Japan International Cooperation Agency (JICA) Department of Transportation and Communications (DOTC)

The Project for Capacity Development on Transportation Planning and Database Management in the Republic of the Philippines

MMUTIS Update and Enhancement Project (MUCEP)

Manual vol. 2

Travel Demand Forecasting

December 2015

ALMEC Corporation Oriental Consultants Global Co., Ltd

TABLE OF CONTENTS

1 INTRODUCTION ...... 1-1 1.1 Background ...... 1-1 1.2 Objectives ...... 1-1 1.3 Structure of the Manual ...... 1-2 1.4 How to use this manual ...... 1-2

2 KEY CONCEPTS ...... 2-1 3 DATABASE DEVELOPMENT ...... 3-1 4 OVERVIEW OF THE FOUR STEP MODEL ...... 4-1 5 TRAVEL DEMAND MODEL FOR METRO MANILA ...... 5-1 5.1 Zoning System ...... 5-1 5.2 Socio-economic Framework ...... 5-3 5.3 Road Network ...... 5-4 5.4 Trip Generation Model ...... 5-11 5.5 Trip Distribution Model ...... 5-11 5.6 Modal Split Model ...... 5-12 5.7 Highway Assignment ...... 5-13 5.8 Origin–Destinationi Data ...... 5-13 5.9 Highway Assignment Result ...... 5-14 6 SKETCH PLANNING ...... 6-1 6.1 Methodology ...... 6-1 6.2 Sample Sketch Planning Model ...... 6-2

APPENDICES Appendix A: Description of the Zoning System Appendix B: Population Trends in MUCEP Area Appendix C: Estimated Car Ownership

LIST OF TABLES

Table 5.1 Traffic Analysis Zones ...... 5-1 Table 5.2 Increase Ratios of GRDP/Capita ...... 5-3 Table 5.3 Schedule of the Road Survey ...... 5-5 Table 5.4 Summary of the Updated Road Links ...... 5-5 Table 5.5 Road Capacity and Maximum Speed by Road Category ...... 5-6 Table 5.6 Parameters for Public Modes ...... 5-6 Table 5.7 Projects Included in the Roadmap for Metro Manila and Surrounding Areas ...... 5-7 Table 5.8 Link Information ...... 5-9 Table 5.9 Link Type (USERFLAG5) for Road Link ...... 5-9

Table 5.10 Link Type (USERFLAG5) for Rail Link ...... 5-10 Table 5.11 Trip Generation and Attraction Models ...... 5-11 Table 5.12 Modal Split Model ...... 5-12 Table 5.13 Modal Split Parameters between Private and Public Modes ...... 5-12 Table 5.14 Total Trips by Mode ...... 5-13 Table 6.1 Description of Zoning System for General Santos City...... 6-3 Table 6.2 Length of Roads in General Santos City by Barangay ...... 6-5 Table 6.3 Passenger Car Equivalent Factors ...... 6-6 Table 6.4 Traffic Volume along National Highways in General Santos City ...... 6-7 Table 6.5 Traffic Growth Rate in Region XII ...... 6-7

LIST OF FIGURES

Figure 2.1 Car–Public Transportation Vicious Cycle ...... 2-2 Figure 2.2 Land Use and Transportation Interaction ...... 2-2 Figure 2.3 Changes in the Transportation System...... 2-3 Figure 2.4 Changes in the Land Use System ...... 2-3 Figure 2.5 Definition of a Trip ...... 2-5 Figure 2.6 Single Trip Entry ...... 2-5 Figure 2.7 Constructing an OD Table ...... 2-6 Figure 3.1 Zoning System ...... 3-2 Figure 3.2 Household Information Survey Form ...... 3-3 Figure 3.3 Member Information Survey Form ...... 3-4 Figure 3.4 Trip Information Survey Form ...... 3-5 Figure 3.5 Trade-off between Sample Size and Cost ...... 3-6 Figure 3.6 Sample Road Network ...... 3-8 Figure 4.1 Four-Step Model ...... 4-1 Figure 4.2 Objectives of the Four-Step Model ...... 4-1 Figure 4.3 Trip Generation ...... 4-2 Figure 4.4 Sample Trip Generation Computation ...... 4-2 Figure 4.5 Trip Distribution ...... 4-3 Figure 4.6 Modal Split ...... 4-3 Figure 4.7 Choice Model ...... 4-4 Figure 4.8 Traffic Assignment ...... 4-5 Figure 5.1 Traffic Analysis Zones within NCR ...... 5-1 Figure 5.2 Traffic Analysis Zones in adjacent Provinces ...... 5-2 Figure 5.3 Population Trends in MUCEP Area ...... 5-3 Figure 5.4 Interface of the BlackVue Software ...... 5-4 Figure 5.5 2015 Network ...... 5-6 Figure 5.6 2025 Network ...... 5-8 Figure 5.7 2035 Network ...... 5-8 Figure 5.8 Transit Data ...... 5-10 Figure 5.9 QV Function ...... 5-13 Figure 5.10 Highway Assignment Results for 2014 ...... 5-14 Figure 6.1 Sketch Planning Model Flow ...... 6-3 Figure 6.2 Traffic Analysis Zones in General Santos City ...... 6-4 Figure 6.3 Road Network Data of General Santos City ...... 6-5 Figure 6.4 Volume-Speed Relationship ...... 6-6 Figure 6.5 Incremental Traffic Assignment...... 6-8 Figure 6.6 Zonal Data ...... 6-9 Figure 6.7 Trip Production Equations ...... 6-10 Figure 6.8 Trip Attraction Equations ...... 6-10 Figure 6.9 Matrix Calibration Application ...... 6-11 Figure 6.10 Matrix Calibration for Car Trips ...... 6-12 Figure 6.11 Calibrated OD Matrices by Mode ...... 6-12 Figure 6.12 Highway Assignment Application ...... 6-13 Figure 6.13 Link Traffic Volumes for Daily Traffic ...... 6-13 Figure 6.14 Link Traffic Volumes for Peak Hour Traffic ...... 6-13 Figure 6.15 Daily Time, Distance, and Speed Skims ...... 6-14 Figure 6.16 Peak-Hour Time, Distance, and Speed Skims ...... 6-14 Figure 6.17 Desire Lines for General Santos City ...... 6-15

ABBREVIATIONS

AADT annual average daily traffic BPR Bureau of Public Roads DOTC Department of Transportation and Communications DPWH Department of Public Works and Highways EDSA Epifanio de los Santos Avenue GDP gross domestic product h hour HIS household interview survey JICA Japan International Cooperation Agency km kilometer LRT Light rail transit LRTA Light Rail Transportation Authority LTFRB Land Transportation Franchising and Regulatory Board MMDA Metropolitan Manila Development Authority MRT 3 Metro Rail Transit Line 3 MRTC Metro Rail Transit Corporation MUCEP MMUTIS Update and Capacity Enhancement Project NCR National Capital Region O-D origin–destination PCEF passenger car equivalent factor PCU passenger car unit PHP Philippine peso PNR Philippine National Railways PT public transportation PUB public utility bus PUJ public utility jeepney RTIA Road Traffic Information Application TAZ traffic analysis zone

The Project for Capacity Development on Transportation Planning and Database Management MANUAL ON TRAVEL DEMAND FORECASTING

1 INTRODUCTION

1.1 Background The acceleration of economic activities and population concentration in Metro Manila and other cities in the Philippines has caused severe social problems such as traffic congestion, traffic accidents, and deterioration of the living environment. The development of the public transportation network is crucial in tackling these problems. In addition, investment in infrastructure development is essential to realize a sustainable economic growth. Metro Manila, in particular, requires a transportation policy to facilitate a modal shift from private cars to public transportation by developing and integrating transportation networks and strengthening linkages between transportation modes. It is within this context that the Government of Japan has provided technical assistance to the Philippines’ Department of Transportation and Communications (DOTC) and other related agencies through the Japan International Cooperation Agency (JICA) in conducting a capacity development project entitled “The Project for Capacity Development on Transportation Planning and Database Management in the Republic of the Philippines.” MUCEP, as the project is known (short for MMUTIS Update and Capacity Enhancement Project), has been carried out for more than four years, starting on 27 September 2011 and completing on 30 November 2015. The overall project goal of MUCEP is to enable the DOTC to prepare a public transportation plan for Metro Manila for strategic corridors by strengthening their capacity in transportation database management and public transportation network planning. Transportation planning requires a multi-disciplinary approach with important considerations given to socio- economic conditions, environment, and sustainability. Toward this end, the project included capacity building in travel demand forecasting carried out through pilot studies. Demand forecasting is a multi-stage process and can use several different techniques at each stage. It is undertaken in order to:

• Estimate the impact of any improvement projects, such as the construction of new roads and rehabilitation of old railways, on the transportation system; and

• Estimate the impact of any policies, such as tolls, fare level of public transportation, truck ban, and road pricing, on the transportation system.

1.2 Objectives This manual on travel demand forecasting aims at providing an easy-to-understand and logical guide to travel demand analysis and modeling as part of transportation planning. Generally, travel demand modeling is complex with variable approaches depending on the type of transportation planning activity. As such, it is suggested that approaches presented in this manual should be carefully evaluated as to their applicability in terms of the goals of the planning activity and the conditions for implementation (i.e., coverage, time frame, finances, data availability, etc.).

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1.3 Structure of the Manual This manual is composed of five chapters, namely: (i) Key Concepts (ii) Database Development (iii) Four-step Model (iv) Sketch Planning Methodology (v) Sample Sketch Planning Model

1.4 How to Use this Manual This manual provides the users with a logical guide and a step-by-step approach for undertaking travel demand analysis and modeling based on the application of established techniques and tools to achieve the required planning results.

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2 KEY CONCEPTS

Cities are locations with high accumulation and concentration of economic activities and are complex spatial structures supported by transportation systems. The most important transportation problems often relate to urban areas, especially when urban transportation systems, for a variety of reasons, cannot satisfy the numerous requirements of urban circulation. Urban productivity is highly dependent on the efficiency of the transportation system, notably to move labor, consumers, and freight between several origins and destinations. The growing complexity of cities has been accompanied by a wide array of urban transportation problems. Problems associated with urban transportation are: (i) Traffic congestion and parking difficulties • Most prevalent transportation problems in large urban agglomerations • Linked with the diffusion of the automobile, which increases parking demand in places often incapable of handling such requirements • Transportation infrastructure developments have often not been able to keep up with the growth of circulation (ii) Public transportation inadequacy • Many public transit systems, or parts of them, are either over or underused; and • During peak hours, crowdedness is creating discomfort for users while low ridership makes many services financially unsustainable, particularly in suburban areas. (iii) Difficulties for pedestrians • These difficulties are either the outcome of intense circulation where pedestrians and vehicles are impairing their respective movements, but also because of a blatant lack of considering pedestrian movements in the physical design of facilities. (iv) Environmental impacts and energy consumption • Pollution, including noise, generated by circulation has become a serious impediment to the quality of life and even the health of urban populations • Energy consumption by urban transportation has dramatically increased and so has the dependency on petroleum. (v) Loss of public space • The majority of roads are publicly owned and accessible. With the increase in traffic volumes, adverse impacts on public activities have been important; • In many cases, street activities (e.g., markets, agoras, parades and processions, games, and community interactions) have shifted to shopping malls, while in other cases, such activities have been abandoned altogether; • Traffic volumes influence the life and interactions of residents and their usage of street space; • More traffic encourages less social interactions and fewer street activities; and

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• Heavy traffic also has adverse impact on human health. In fact, people tend to walk and cycle less when traffic is heavy. (vi) Accidents and safety • Growing circulation in urban areas has been linked to a growing number of accidents and fatalities, especially in developing countries. (vii) Land consumption • As between 30% and 60% of a metropolitan area can be devoted to transportation, a large amount of land can be considered as wasted by an over-reliance on some forms of urban transportation. A vicious cycle between car and public transportation exist wherein greater use of private cars reduces the demand for public transportation. Figure 2.1: Car–Public Transportation Vicious Cycle

Source: JICA Project Team The concept of land use–transportation interaction asserts that land use and transportation systems are tightly interconnected. Any change in either variable will have an impact on the other. Figure 2.2: Land Use and Transportation Interaction

Source: JICA Project Team

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Figure 2.3: Changes in the Transportation System

Source: JICA Project Team Figure 2.4: Changes in the Land Use System

Source: JICA Project Team The challenges in integrating land use and transportation are: (i) Weak integration of the social dimensions of urban planning in existing systems; (ii) Weak coordination mechanisms among local governments and the higher planning authorities

• Effective land-use planning has two components: long-term comprehensive planning to deal with metropolitan scale issues and site or locality-specific plans. (iii) Lack of integrated planning models that are capable of addressing air pollution, transportation, and health issues as decision-support tools for a comprehensive planning process.

• There is a need for good data but also for models that are not overly data-hungry.

• Scope for development of ‘sketch planning’ methods (iv) Lack of effective urban development management skills, which are required to manage the implementation of land use/ transportation plans and policies.

• Significant technical capacity, preferably at a local level, is required to provide

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responsive urban management. (v) Lack of timely provision of infrastructure

• Transportation is a useful instrument for structuring land uses within an appropriate planning framework. In rejecting the former paradigm of building capacity, transportation planners have turned increasingly to managing both demand and the transportation system. Building roads has produced a car-oriented society in which the other modal alternatives have little opportunity to co-exist. Car ownership is beyond the ability of the transportation planner to control directly, and the question remains if it should. But car use and ownership are affected by land use and density, both elements that planners can affect. High population densities, in particular, favor walking, bicycling, and public transit use. A great deal of attention in planning is being paid to densification and integration. These include concentrating development along well-served transportation corridors (transit- oriented development) and increasing densities in areas undergoing rehabilitation. Managing the demand for travel is made up of a large number of small interventions that cumulatively can have an impact on car use, but in particular improve the livability of cities. Some of the well-practiced and successful interventions include: (i) Implementing park and ride schemes; (ii) Carrying out traffic calming measures; (iii) Providing priority lanes for buses and high occupancy vehicles; (iv) Adopting alternate work schedules; (v) Promoting bicycle use; (vi) Sharing cars; (vii) Enhancing pedestrian areas; (viii) Improving public transit; and (ix) Managing parking. Sustainable development is defined as the "development which meets the needs of the present without compromising the ability of future generations to meet their own needs“ (Brundtland Commission in 1987). A sustainable city must offer to its population a suitable urban environment, employment, food, housing, and transportation without compromising the welfare of the future population of that city. There are three dimensions of sustainable development, as follows: (a) Intergenerational Equity: The success of cities of the future will largely depend upon the legacy on current cities on resources and the environment. National capital assets passed on to the next generation must be at least of equal value. (b) Social Equity: This implies a fair and equitable distribution of resources among the current generation. In terms of the urban environment, the city should provide a place of equal opportunity and not be an agent of segregation.

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(c) Spatial Responsibility: This involves the idea that the city has a "footprint" which is considerably larger than the area it occupies. This includes supply of resources and wastes, whose impacts must be considered in the total space a city occupies. Transportation planning is the functional area within transportation engineering that deals with the relationship of land use to travel patterns and demands. It involves the planning, evaluation, and programming of transportation facilities, including roadways, transit terminals, parking, pedestrian facilities, bikeways, and goods movement. A trip is a one-way movement from a point of origin to a point of destination. Home-based trips are trips that either start from or end at the home. Trips from home to work are referred to as home-based work (HBW) trips. Trips from home to school are referred to as home-based school (HBS) trips. Other types of trips originating from home are referred to as home-based others (HBO). Finally, trips that do not have home as their origin or destination are referred to as non-home-based (NHB) trips. Figure 2.5: Definition of a Trip

Home Shop

Work

Source: JICA Project Team Trips captured in the conduct of household interview surveys (HIS) can be classified based on: (i) Purpose (Work, School, Shop, Others); (ii) Time of day (AM, PM, peak, off-peak); and (iii) Person type (income, car ownership, family size, accessibility, etc.). The origin-destination (OD) data is a collection of typical day trip activities of residents within the study area. Figure 2.6: Single Trip Entry

OD Table To Work, Starting at 7:00 am D 1 2 3 . . j . . Person X O Origin Zone: 2 1 Destination Zone: 3 Purpose: To Work 2 Time of Departure: 7:00 am …. i . . .

Source: JICA Project Team

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Figure 2.7: Constructing an OD Table

D D 1 2 3 . . j . . 1 2 3 . . j . . O D O 1 2 3 . . j . . 1 O D 1 2 3 . . j . . 1 O D 2 1 2 3 . . j . . 1 1 O D 2 O 1 2 3 . . j . . i 1 D 2 O 1 2 3 . . j . . i 1 D . 2 O 1 2 3 . . j . . 2 i 1 D . . 2 O 1 2 3 . . j . . i 1 . . 2 . 1 . i . . 2 i . i . . 2 . i . . . i ......

Source: JICA Project Team Transportation demand models refer to a series of mathematical equations that are used to represent how choices are made when people travel. Travel demand occurs as a result of thousands of individual travelers making individual decisions on how, where, and when to travel. These decisions are affected by many factors such as family situations, characteristics of the person making the trip, and the choices (destination, route, and mode) available for the trip. Mathematical relationships are used to represent (model) human behavior in making these choices. Models require a series of assumptions in order to work and are limited by the data available to make forecasts. The coefficients and parameters in the model are calibrated using existing data. Normally, these relationships are assumed to be valid and to remain constant in the future. Travel demand modeling was first developed in the late 1950s. Since then the modeling process has been modified to add additional techniques to deal with other problems that have arisen, such as transit, land-use issues, and air quality analysis. Models are important because transportation plans and investments are based on what the models say about future travel. Models are used to estimate the number of trips that will be made on a transportation systems alternative at some future date. These estimates are the basis for transportation plans and are used in analyzing major investments and environmental impact statements, as well as in setting priorities for investments. Models provide forecasts only for those factors and alternatives that are explicitly included in the equations of the models. If the models are not sensitive to certain policies or programs (i.e., policy-sensitive), they will not show the effects of such policies.

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3 DATABASE DEVELOPMENT

Generally, the development of database for use in travel demand forecasting involves the following items: (i) Breakdown of the area which requires the prediction of future travel demand into study zones that can be accurately described by a few variables (Zoning Design); (ii) Collection of existing socio-economic data for the study area; (iii) Conduct of person-trip (PT) surveys to establish the present travel patterns, specifically, person OD trips; (iv) Conduct of other traffic surveys to calibrate the model for the base year (e.g., screen line traffic counts); and (v) Conduct of land use surveys to establish land use development patterns The zoning design requires considering the decision-making context, the schemes to be modeled, and the nature of trips of interest in the study. The study area should have majority of origin and destination trips inside it. The study area should be somewhat bigger than the specific area of interest. The Study Area will be comprised of zones. The zoning system is a way of aggregating trips into manageable chunks for modeling purposes. The Traffic Analysis Zone (TAZ) is a basic unit of a zoning system where each zone is a point of origin and destination for trips. The zoning criteria that are used in establishing the zone boundaries of Traffic Analysis Zones (TAZ) are: (i) Zoning size must be such that aggregation errors are minimized; (ii) Zoning system must be compatible with other administrative divisions, particularly with census zones; (iii) Zones should be as homogeneous as possible in their land use and/or population composition; (iv) Zone boundaries must be compatible with cordons and screen lines and with those of previous zoning systems; (v) Shape of the zones should allow easy identification of centroid connectors; (vi) Zones do not have to be of equal size; and (vii) Zone sizes must consider population distribution; that each zone may have similar population (homogeneity). Typical surveys that are undertaken in the development of a travel demand forecasting model are: (i) Infrastructure and existing services inventories; (ii) Land use inventories; (iii) Household interview surveys (HIS); and (iv) Socio-economic information collection.

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Figure 3.1: Zoning System

Source: MMUTIS 1996

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The Household Interview Survey (HIS) is the most valuable source of data for travel demand analysis and is certainly the most costly and time-consuming to conduct. The objectives of the HIS or Person-Trip (PT) Survey are: (i) To capture the socio-economic profile of households in the study area; and (ii) To establish detailed trip information of household members in the study area. Figure 3.2: Household Information Survey Form FORM 1: HOUSEHOLD INFORMATION

(1) Name ______Last Name First Name M.I.

(2) Address of ______household No. Street Barangay ______Municipality/City Telephone No. (optional)

(Note: Interviewers should inform interviewees that their names and addresses are needed only for follow- ups and checking of interviewer’s activities and will not be part of the database.)

(3) How many members are there in your household?

60 Years Old and Household Under 5 5–59 Years Old Above Helpers Without With Without With Without With Without With disability disability disability disability disability disability disability disability Male Female Total

(4) What is your total (5) How many vehicles (6) How many of your household monthly household are owned/rented vehicles are parked in your income (PHP)? by your household? garage/ near your house? (Encircle one item)

1. Below 5,000 NO. OF UNITS NO. OF − TYPE TYPE 2. 5,000 9,999 OWNED RENTED UNITS − 3. 10,000 14,999 1. Bicycle Bicycle − 4. 15,000 19,999 2. Motorcycle Motorcycle − 5. 20,000 24,999 3. Car/Jeep Car/Jeep − 6. 25,000 29,999 4. Pedicab Pedicab − 7. 30,000 34,999 5. Tricycle Tricycle − 8. 35,000 39,999 6. Taxi Taxi − 9. 40,000 49,999 7. Filcab Filcab − 10. 50,000 59,999 8. HOV HOV − 11. 60,000 79,999 9. Jeepney Jeepney − 12. 80,000 99,999 10. Minibus Minibus − 13. 100,000 149,999 11. Standard Bus Standard Bus − 14. 150,000 199,999 12. School/Co./ School/Co./ 15. 200,000−299,999 Tourist Bus Tourist Bus 16. 300,000−499,999 13. Pick-up/Delivery Pick-up/Delivery Van 17. Above 500,000 Van 14. Truck Truck 15. Trailer Trailer 16. Others Others

(7) Ownership of house and land (8) Length of stay in current residence Owned Rented PHP/Month House ______No. of years ______Land ______

(9) What is your previous residential address? Source: JICA Project Team

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Figure 3.3: Member Information Survey Form

FORM 2: HOUSEHOLD MEMBER INFORMATION

INSTRUCTION: To be completed by every household member aged 5 years and above.

(1) Name ______Last Name First Name M.I.

(2) Age _____ (3) Gender Male Female (4) Differently Abled Yes No

(5) Work address ______No. Street Barangay ______Municipality/City Province

(6) School address ______No. Street Barangay ______Municipality/City Province

(7) Occupation (8) Employment sector (9) Monthly income (PHP) (Encircle one item) (Encircle one item) (Encircle one item) 1. Official of Govt. & Special 1. Agriculture, Hunting & Forestry 1. Below 5,000 Interest Org., Corporate Exec., 2. Fishing − Manager 3. Mining & Quarrying 2. 5,000 9,999 2. Professional 4. Manufacturing 3. 10,000−14,999 3. Technical & Associate 5. Electricity, Gas & Water Supply 4. 15,000−19,999 Professionals 6. Construction 5. 20,000−24,999 4. Clerical Staff 7. Wholesale & Retail Trade; Repair 6. 25,000−29,999 5. Service Worker, Shop & of Motor Vehicles, Personal & Market Worker Household Goods 7. 30,000−34,999 6. Farmer, Forestry Worker & 8. Hotels & Restaurants 8. 35,000−39,999 Fisherman 9. Transport, Storage & Comm. 9. 40,000−49,999 7. Trader & Related Worker 10. Financial Intermediation 10. 50,000−59,999 8. Plant & Machine Operator & 11. Real Estate Development, Rental − Assembler and Sale 11. 60,000 79,999 9. Laborer & Unskilled Worker 12. Public Admin. & Defense; 12. 80,000−99,999 10. Student (Elem.) Compulsory Social Security 13. 100,000−149,999 11. Student (H.S. & Univ.) 13. Education 14. 150,000−199,999 12. Housewife 14. Health & Social Work − 13. Unemployed 15. Other Community, Social & 15. 200,000 299,999 14. Others (specify)______Personal Services 16. 300,000−499,999 16. Private Households 17. Above 500,000 17. Extraterritorial Organizations

(10) State the type of driver’s license held

Student Non-Prof. Professional None

(11) Number of vehicles for your own use

Bicycle: Motorcycle: Car/Jeep: Others: a

(12) Work hours Fixed Time Flexible Time

A pilot study is examining the possibility of using mobile phones to complement household interview

Source:surveys. JICA ItProject involves Team the analysis of the Call Detail Record (CDR), which shows call durations, as well as approximate locations where calls were made and text messages were sent from.

(13) Are you willing to participate in the pilot study for Metro Manila? Rest assured that no information to identify you or the location of your house is kept in the CDR. Data collection will also stop when the household survey ends. All data will be treated with utmost confidentiality.

Yes. Mobile phone #: ______Carrier: ______or Globe/SMART

No I have no cellular phone.

Source: JICA Project Team

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Figure 3.4: Trip Information Survey Form

Origin address Household No. a No. Street / Block Member code:

b Origin Barang ay Municipality / City Trip No. 1 of 1

Landmark Institution of origin and destination 1. Residence Institution code Type code c d e 2. Commercial Institution Departure time : 3. Office / Bank at origin and mode Hours Minutes f Mode code g 4. Factory / Warehouse 1st transf er point 5. School / University 6. Park / Recreational Place If others, specify; 7. Medical / Welfare Bus stop, station, landmark, location, etc. h 8. Religious / Social Departure time : 9. Wholesale / Retail shop Hours Minutes i Mode code j 10. Restaurant / Entertainment 2nd transf er point 11. Others Transfer point(s) Type of If others, specify; Departure time(s) Bus stop, station, landmark, location, etc. k origin and destination Departure : 1. Home (Answ er in Form 1-(2)) Travel mode(s) time Hours Minutes l Mode code m 2. Workplace / School 3rd transf er point (Answ er in Form 2-(5)/(6))

3. Others If others, specify; Bus stop, station, landmark, location, etc. n Departure time : Travel mode Hours Minutes o Mode code p 1. Walking 15. Standard Bus Arrival time : 2. Bicycle - w /o aircon at destination 3. Motorcycle 16. Standard Bus Hours Minutes q If others, specify; Destination address - driver - w / aircon 4. Motorcycle 17. School Bus - passenger 18. Company Bus No. Street / Block 5. Car/Jeep 19. Tourist Bus - driver 20. Pick-up / Barang ay Municipality / City 6. Car/Jeep Delivery Van Destination - passenger 21. Truck

7. Pedicab 22. Trailer Landmark 8. Tricycle 23. LRT / MRT 9. Taxi 24. PNR 10. Filcab 25. Water Institution code Type code r s t 11. HOV Transport 12. Jeepney 26. Airplane Trip purpose Trip purpose code If others, specify; u 13. Minibus 27. Others - w /o aircon Trip purpose of companion, 14. Minibus if any Trip purpose code If others, specify; v - w / aircon Trip cost PHP w 1. Parking lot Trip purpose PHP Type of parking facility and 2. On-road, authorized fee 3. On-road, unauthorized Fee paid x y 1. To home 4. Inside building or house premises 2. To w ork 1. Travel time 3. Convenience 5. Safety z Reason for modal choice 3. To school / Education 2. Comfort 4. Cost 6. No other choice 4. Private Business aa 5. Employer's Business Travel time 1. Very bad 2. Bad 3. OK 4. Good 5. Very good

6. Private - Medical ab 7. Private - Social Comf ort 1. Very bad 2. Bad 3. OK 4. Good 5. Very good

8. Private - Eating ac Convenience Very bad Bad OK Good Very good 9. Private - Shopping Trip 1. 2. 3. 4. 5. 10. Private - Worship assessment ad 11. Private - Recreation Cos t 1. Very bad 2. Bad 3. OK 4. Good 5. Very good 12. To send/pick up other ae Safety 1. Very bad 2. Bad 3. OK 4. Good 5. Very good family members or friends 13. Others af Overall 1. Very bad 2. Bad 3. OK 4. Good 5. Very good

Source: JICA Project Team

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A sampling design aims at ensuring that the data to be examined provide the greatest amount of useful information about the population of interest at the lowest possible cost. The problem is how to use the data (i.e., expand the values in the sample) in order to make correct inferences about the population. The greatest difficulties in the conduct of sampling surveys are:

• How to ensure a representative sample; and • How to extract valid conclusions from the sample. Common sampling methods that are employed in the conduct of HIS are: (a) Simple Random Sampling: Simplest and basic method. (b) Stratified Random Sampling: Subdividing the population into homogeneous strata (with respect to the stratifying variable), then random sampling is conducted inside each stratum using the same sampling rate. (c) Choice-based Sampling: Stratifying the population based on the results of the choice process under consideration. This is fairly common in transportation planning, with the advantage that data may be produced at a much lower cost. The drawback is that the sample may not be random and therefore there is a risk of bias in the expanded values. Sources of errors from household surveys include: (a) Sampling Error: Always present in dealing with samples. It does not affect the expected values but influences the variability and confidence level. (b) Sampling Bias: This is caused by mistakes either when defining the population of interest or when selecting the sampling methods and maybe avoided or eliminated by taking extra care during sampling design and data collection. One critical aspect in survey planning is the determination of sample size. There is no straightforward or objective answer to the calculation of sample size in every situation. It must be produced by the analyst after careful consideration of the problem at hand. There is a trade-off between sample size and overall survey cost. If the sample size is too small, the degree of confidence on the data will be very low. On the other hand, if the sample size is too big, the degree of confidence on the data will be very high, but the survey cost will be impractically high. Figure 3.5: Trade-off between Sample Size and Cost

High cost High degree of confidence

Low cost Low degree of confidence

Small Large Sample Size

Source: JICA Project Team

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The number of samples may be computed by using the following formula:

CV22 Z = α n 2 E CV = σ / μ

Where CV is the coefficient of variation, E is the level of accuracy (expressed as a proportion) and Zα is the value of the standard normal variate for the confidence level (α) required. The types of errors encountered in household surveys, include: (a) Measurement Errors: Errors in getting base year data. (b) Sampling Errors: Models must be estimated using finite data sets. (c) Specification Errors: Phenomenon being modeled is not well understood due to simplifications. (d) Transfer Errors: Spatial and temporal transfers. (e) Aggregation Errors: This arises basically out of the need to make forecasts for groups while modeling needs to be done at the individual level. Types: data aggregation, aggregation of alternatives, model aggregation. A network is usually modeled as a directed graph. It consists of a system of nodes and links joining them. Most nodes are taken to represent junctions and the links stand for homogeneous stretches of road between junctions. Links are characterized by attributes such as: (i) Length; (ii) Travel speeds (in speed-flow curves); (iii) Link capacity (in PCU per hour); (iv) Additional information; (v) Type of road; (vi) Road width, number of lanes; (vii) Turn penalties; (viii) Type of junctions; and (ix) Signal phasing. A subset of the nodes is associated with zone centroids and a subset of the links to centroid connectors. Turning movement controls may be modeled as penalties and/or turn restrictions, e.g., no entry. Movement controls can be represented by dummy links.

3-7 The Project for Capacity Development on Transportation Planning and Database Management MANUAL ON TRAVEL DEMAND FORECASTING

Figure 3.6: Sample Road Network

Source: JICA Project Team

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4 OVERVIEW OF THE FOUR-STEP MODEL

The Four-Step Model is a sequential process for generating travel demand forecasts with the following steps: (a) Trip Generation: Calculate the number of trips starting in each zone for a particular trip purpose. (b) Trip Distribution: Produce a table of the number of trips starting in each zone and ending up in each of the zones. (c) Modal Split: Complete the allocation of the various trips among the available transportation systems (bus, train, pedestrian, and private vehicles). (d) Traffic Assignment: Identify the specific routes on each transportation system that will be selected by the travelers. Figure 4.1: Four-Step Model

Future Base-Year Zone Planning Data Networks Data

Database

Trip Generation How many person trips?

Trip Distribution Where are they going?

Modal Split What mode are they using? Iteration Output Trip Assignment What route will they take?

Evaluation

Source: JICA Project Team The key objective of the four-step model is to determine the future traffic volumes on the road network under various assumptions of road and land use changes. Figure 4.2: Objectives of the Four-Step Model

Existing OD Matrix Future OD Matrix

What are the future trip ? ? patterns?

?

What are the ? future traffic ? volumes on the road network? Existing Network Future Network Source: JICA Project Team 4-1 The Project for Capacity Development on Transportation Planning and Database Management MANUAL ON TRAVEL DEMAND FORECASTING

The total traffic volume in the future will be composed of the following components: (i) Existing traffic; (ii) Traffic due to natural population increase; (iii) Traffic due to proposed development; and (iv) Traffic due to other developments. Trip generation is the first step in the conventional four-step transportation planning process, widely used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone. Trip generation uses trip rates that are averages for a large segment of the study area. Trip productions are based on household characteristics such as the number of people in the household and the number of vehicles available. For example, a household with four people and two vehicles may be assumed to produce 3.00 work trips per day. Trips per household are then expanded to trips per zone. Trip attractions are typically based on the level of employment in a zone. For example, a zone could be assumed to attract 1.32 home-based work trips for every person employed in that zone. Trip generation is used to calculate person trips. Figure 4.3: Trip Generation

Trip Production Trip Attraction

i j

Population

Employee

Source: JICA Project Team

Figure 4.4: Sample Trip Generation Computation

?

Σ Total Person Trips = (Floor Area i x Trip Rates i) where i = Land Use Classification

Land Use Trip Rates Classification Production Attraction Unit Office 0.0027 0.0176 trips / sq.m. of GFA Commercial 0.0576 0.0735 trips / sq.m. of GFA

Hotel 2.00 2.55 trips / hotel room Residential 2.42 1.52 trips / dwelling unit Mixed Use 0.0172 0.0243 trips / sq.m. of GFA

Source: JICA Project Team 4-2 The Project for Capacity Development on Transportation Planning and Database Management MANUAL ON TRAVEL DEMAND FORECASTING

Trip distribution is the second component in the traditional four-step transportation planning (or forecasting) model. This step matches trip makers’ origins and destinations to develop a “trip table,” a matrix that displays the number of trips going from each origin to each destination. Figure 4.5: Trip Distribution

i j

Population

Employee

Source: JICA Project Team Mode choice analysis is the third step in the conventional four-step transportation planning model. Trip distribution's zonal interchange analysis yields a set of origin– destination tables which tell where the trips will be made; mode choice analysis allows the modeler to determine what mode of transportation will be used. Figure 4.6: Modal Split

800 person-trips 400 cars @ 2 persons/car

2,000 40% person-trips

800 person-trips 200 buses 40% @ 40/bus

Going to Zone A

20% 400 person-trips LRT

Source: JICA Project Team

Mode choice is one of the most critical parts of the travel demand modeling process. It is the step where trips between a given origin and destination are split into trips using transit, trips by car pool or as automobile passengers and trips by automobile drivers. A utility function measures the degree of satisfaction that people derive from their choices and a disutility function represents the generalized cost that is associated with each choice. The most commonly used process for mode split is to use the 'Logit' model. This involves a comparison of the "disutility" or "utility" of travel between two points for the different

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modes that are available. Disutility is a term used to represent a combination of the travel time, cost, and convenience of a mode between an origin and a destination. It is obtained by placing multipliers (weights) on these factors and adding them together. Figure 4.7: Choice Model

Individual Level of Probability Socio- Service to chose Economic of each mode i Profile + Mode =

PBus

Travel Time Travel Cost PRail Income Frequency Sex etc. etc. Pcar

Source: JICA Project Team Disutility calculations may contain a "mode bias factor" which is used to represent other characteristics or travel modes that may influence the choice of mode (such as a difference in privacy and comfort between transit and automobiles). The mode bias factor is used as a constant in the analysis and is found by attempting to fit the model to actual travel behavior data. Generally, the disutility equations do not recognize differences within travel modes. For example, a bus system and a rail system with the same time and cost characteristics will have the same disutility values. There are no special factors which allow for the difference in attractiveness of alternative technologies. Once disutilities are known for the various mode choices between an origin and a destination, the trips are split among various modes based on the relative differences between disutilities. The logit equation is used in this step. A large advantage in disutility will mean a high percentage for that mode. Mode splits are calculated to match splits found from actual traveler data. Sometimes a fixed percentage is used for the minimum transit use (percent captive users) to represent travelers who have no automobile available or are unable to use an automobile for their trip. Trip assignment, traffic assignment, or route choice concerns the selection of routes (alternative called paths) between origins and destinations in transportation networks. It is the fourth step in the conventional transportation planning model. To determine facility needs, as well as costs and benefits, the number of travelers on each route and link of the network should be known. Once trips have been split into highway and transit trips, the specific path that they use to travel from their origin to their destination must be found. These trips are then assigned to that path in the step called traffic assignment.

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Figure 4.8: Traffic Assignment

800 cars

50% = 200 cars

Origin

30% = 120 cars

20% = 80 cars

Destination

Source: JICA Project Team The process first involves the calculation of the shortest path from each origin to all destinations (usually the minimum time path is used). Trips for each O-D pair are then assigned to the links in the minimum path and the trips are added up for each link. The assigned trip volume is then compared to the capacity of the link to see if it is congested. If a link is congested the speed on the link needs to be reduced to result in a longer travel time on that link. Changes in travel times mean that the shortest path may change. Hence, the whole process is repeated several times (iterated) until there is equilibrium between travel demand and travel supply. Trips on congested links will be shifted to uncontested links until this equilibrium occurs. Traffic assignment is the most complex calculation in the travel modeling sequence, and there is a variety of ways in which it is done to keep computer time to a minimum. The U.S. Bureau of Public Roads (BPR) function is the most commonly used function for relating changes in travel speed to increases in travel volume. The BPR function is specified as follows:

where: Tf = final link travel time To = original (free-flow) link travel time alpha = coefficient (often set at 0.15) V = assigned traffic volume C = the link capacity beta = exponent (often set at 4.0)

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Traffic assignment models usually compute the shortest path based on generalized travel cost on the network. In transportation economics, the generalized cost is the sum of the monetary and non-monetary costs of a journey. Monetary (or "out-of-pocket") costs might include a fare on a public transportation journey, or the costs of fuel, wear and tear, and any parking charge, toll or congestion charge on a car journey. Non-monetary costs refer to the time spent undertaking the journey. Time is converted to a money value using a value of time figure, which usually varies according to the traveler’s income and the purpose of the trip. The generalized cost is equivalent to the price of the good in supply and demand theory, and so demand for journeys can be related to the generalized cost of those journeys using the price elasticity of demand. Supply is equivalent to capacity (and, for roads, road quality) on the network.

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5 TRAVEL DEMAND MODEL FOR METRO MANILA

5.1 Zoning System The Traffic Analysis Zones (TAZs) for Metro Manila are organized according to the zoning system shown below.

Table 5.1: Traffic Analysis Zones

Number of Zones Zoning System MUCEP Study Area Outside the Total NCR Provinces Study Area Small Zone 272 82 67 432 Medium Zone 24 51 14 89 Large Zone 1 4 3 8 Source: JICA Project Team

Based on the Small Zone system, NCR is subdivided into 272 zones, while the areas in the adjacent provinces of Bulacan, Rizal, Cavite, and Laguna are subdivided into 82 zones. Medium and large zones are set based on the boundary of a municipality/ city and the boundary of a province, respectively. The description of the zoning system is presented in Appendix A. Figure 5.1: Traffic Analysis Zones in Adjacent Provinces

Source: JICA Project Team

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Figure 5.2: Traffic Analysis Zones within NCR

Source: JICA Project Team

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5.2 Socio-economic Framework 1) Population Trend Population trends in the MUCEP area are shown in Figure 5.3. Population data for 2014, 2025, and 2035 are shown in Appendix B. Figure 5.3: Population Trends in MUCEP Area Population Trend 35,000,000 Pop_Night 30,000,000 Pop_Day 25,000,000 Pri_Night 20,000,000 Pri_Day 15,000,000 Sec_Night Sec_Day 10,000,000 No. of Population ofNo. Ter_Night 5,000,000 Ter_Day 0 Pupil_Night 2014 2020 2025 2030 2035 Pupil_Day Year

Source: JICA Project Team 2) Car Ownership Rate Trip patterns are generally different between car-owning and non-car-owning households. Private car choice rate of car-owning households is higher than that of non- car-owning household. In MUCEP, the difference in trip patterns by car-owning households is confirmed through an HIS analysis. The number of car-owning households in the future is estimated through an HIS analysis using the model below. The estimated car ownership rate is shown in Appendix C.

COR =AI × 0.000008307

Where: CORi : Car-owning Household Rate in Zone i

AIi : Average Household Income in Zone i And,

AI =AI ×GRDP

AI0i : Base Year (2014) Average Household Income in Zone i GRDP: Increase Ratio of GRDP/capita in Target Year by 2014 Table 5.2: Increase Ratios of GRDP/Capita

Year Increase Ratio of GRDP/Capita by 2014 2014 1.00 2025 1.80 2035 2.93 Source: JICA Project Team

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5.3 Road Network 1) Road Inventory Survey A road inventory survey was conducted in MUCEP to update the existing road network. For this survey, BlackVue was used for capturing the roads for profiling, a road survey form, and ArcGIS for digitizing, validating, and checking the links of the road network shapefiles. The survey was conducted in the MUCEP study area, which are the entire Rizal and Metro Manila, as well as some cities and municipalities of Cavite, Laguna, and Bulacan provinces. The schedule of road survey was from 8 a.m. to 4 p.m., five days a week excluding holidays. Updating the GIS database of existing roads was divided into three parts: road survey, road survey inventory, and updating of the road network shapefile. The road survey was done with the use of BlackVue dash cameras to capture road profiles which will be used in filling out the survey form which is the second part. The survey form contains the information to every road link within the boundaries of the MUCEP study area. Information such as link name and nodes are based on the existing shapefile, while those that are visible on the BlackVue dash cameras are width, center median, road parking, pavement, and road marks. The BlackVue also comes with a GPS map viewer, as shown in the figure below, to keep track of the location of cameras, which helped in determining the road names and identifying new or missing links in the road network. Road survey in Bulacan, Rizal, Laguna, and Cavite was done in July 2015, while that in Metro Manila was divided into north (July 2015) and south (August 2015). Figure 5.4: Interface of the BlackVue Software

Source: JICA Project Team 5-4 The Project for Capacity Development on Transportation Planning and Database Management MANUAL ON TRAVEL DEMAND FORECASTING

2) Updating the Road Network The table below shows the summary of the road network update, wherein 748 are identified as missing links, 284 as revised links, and 2,810 as existing links. Missing links pertain to links that exist but are not digitized or recorded in the existing road network data. In addition, links, such as newly built overpasses and underpasses, are also considered missing links. Revised links, on the other hand, are links that are included in the road network data but are modified due to the changes in nodes that connect the existing to the missing links. Lastly, existing links are those that are present in the road network data and are not modified. In addition, road capacity and maximum speed was updated based on the number of lanes which were identified from the road inventory survey. They are summarized in Table 5.5. Table 5.3: Schedule of the Road Survey July August Area 1st 2nd 5th 1st 2nd 3rd Week 4th Week 3rd Week 4th Week 5th Week Week Week Week Week Week Metro Manila

Rizal

Bulacan

Laguna

Cavite Source: JICA Project Team

Table 5.4: Summary of the Updated Road Links

Area Missing Link Revised Link Existing Link Metro Manila 300 126 2,124 Rizal 146 30 122 Bulacan 10 12 238 Laguna 171 58 118 Cavite 121 58 208 Total 748 284 2,810 Source: JICA Project Team

The rail networks in Metro Manila, which comprises three mass transit systems and the PNR, are also included in the MUCEP network. Table 5.6 show the link parameters of public modes. The fares are not the same as current fares as a result of model calibration.

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Table 5.5: Road Capacity and Maximum Speed by Road Category Carriageway Capacity 1-way Maximum Speed Area Road Category Type pcu/day/lane (km/h) Local road Single 2,200 30 Inside EDSA Secondary Single 4,400 40 Primary Single 6,600 45 Secondary Single 7,700 50 Outside EDSA Inside Primary Single 8,250 60 MM Secondary Divided 14,000 70 (including EDSA) Primary Divided 16,500 80 Local road Single 8,000 30 Outside MM Secondary Single 11,000 55 Primary Single 15,400 60 Access / egress Single 15,000 80 Urban / Intercity Expressway Single 17,000 80 Expressway Divided 20,000 100 Note: Based on MMUTIS and MUCEP updated by JICA Project Team where appropriate

Table 5.6: Parameters for Public Modes

Parameter Description LRT-1 LRT-2 MRT-3 PNR Jeepney Bus Average Speed (km/h) 30.0 30.0 26.0 26.0 - - Boarding Fare (PHP/boarding) 7.5 7.5 6.5 5.0 - - Additional Fare (PHP/km) 0.8 0.8 0.9 0.4 1.4 1.8 Access Walk Speed (km/h) 4.0 4.0 4.0 4.0 - - Source: JICA Project Team

Figure 5.5: 2015 Network

Road Network Rail Network Source: JICA Project Team

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1) Future Network The networks in 2025 and 2035 are prepared as future networks. The future networks include new road projects, updating existing roads, new railway project, and extension of the existing railways, which were proposed by the JICA roadmap study (“Roadmap for Transport Infrastructure Development for Metro Manila and Its Surrounding Areas (Region III and Region IV-A)”). Table 5.7 lists the included projects and are presented in Figure 5.6 and Figure 5.7. Table 5.7: Projects Included in the Roadmap for Metro Manila and Surrounding Areas

Year Road/Rail Project Code Project name 2025 Network Road Ex-1 Segments 9 & 10 Ex-2,3 NLEX-SLEX connector Ex-4,5 Skyway Stage 3 Ex-6 NAIA Expressway Ex-12 Dike road Ex-13 Calamba-Las Pinas Ex-15 CALA Expressway Ex-18 Plaridel Bypass Rail LRT1-2 LRT1 Extension LRT2-2 LRT2 Extension MRT7-2 MRT7 M-5 Alabang Monorail NSCR North-South Commuter Rail 2035 Network Road Ex-7 Makati Expressway Ex-8 R-4 Expressway Ex-9 R-7 Expressway Ex-10 C-6 North Section Ex-11 C-5 Expressway Ex-14 Daang Hari Expressway Ex-16 CAVITEX Extension Ex-17 Tarlac Center Expressway Ex-19 NLEX Phase 3 Ex-20 CLEX Ex-21 2nd Pan Philippine Highway Ex-22 SLEX Extension R-1-40 Primary road packages Rail LRT1-3 LRT1 North Extension LRT2-3 LRT2 West Extension KRT3-1 MRT3 South Extension MRT3-2 MRT3 North Extension MRT-NS-1,2 MRT EDSA Subway M-1 Ortigas Monorail M-2 Pasig Monorail M-4 Marikina Monorail M-6 Cavite Monorail Source: Roadmap for Transport Infrastructure Development for Metro Manila and Its Surrounding Areas (Region III and Region IV-A), 2013

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Figure 5.6: 2025 Network

Road Network Rail Network Source: JICA Project Team Figure 5.7: 2035 Network

Road Network Rail Network Source: JICA Project Team

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2) Link Information The link that presents a road section or a rail segment has information is shown in Table 5.8. Table 5.8: Link Information Item Explanation A Node number i B Node number j LINKNAME Link name DISTANCE Link distance (km) VMAX Maximum velocity (km/h) CAP Link capacity (pcu). See Table 5.5. QV QV Type. 1: Road, 2: Rail, 3: EDSA LNKDIR 1: One-way road (Node i to j), 2: Two-way road FARE1 Toll for motorcycle (PHP) FARE2 Toll for private car (PHP) FARE3 Jeepney fare and Rail fare (PHP) FARE4 Bus fare and Rail fare (PHP) FARE5 Toll for truck (PHP) DIRFLAG1 Directional control flag for motorcycle 0: passable both ways, 1: not passable from i to j, 2: not passable from j to I, 3: not passable both ways DIRFLAG2 Directional control flag for private car DIRFLAG3 Directional control flag for Jeepney DIRFLAG4 Directional control flag for bus DIRFLAG5 Directional control flag for truck ROADFLAG 0: Road link, 1: Expressway link, 3: Rail link USERFLAG1 0: Road and Expressway, 1: Access link to rail, 2: Railway, 3: Rail station USERFLAG2 Not use USERFLAG3 Not use USERFLAG4 0: Zone connector, 1: 2015 Net, 2: 2025 Net, 3: 2035 Net USERFLAG5 Link type or Project code, See Table 5.9. Source: JICA Project Team Table 5.9: Link Type (USERFLAG5) for Road Link Link Type - Description Code Link Type - Description Code Centroid Connector 0 Ex11 C5Ex 61 Local Road (MM) 1 Ex7 MAKATI 62 Secondary Road (MM) 2 Ex8 R4Ex 63 Primary Road (MM) 3 Ex9 R7Ex 64 Local Road (Outside) 11 Ex6 NAIA Ex 65 Secondary Road (Outside) 12 Ex14 Daan Hari 66 Primary Road (Outside) 13 Ex22 SLEX Extension 67 NLEX 51 Ex13 Calamba-Las Pinas 68 SCTEX 52 Ex16 CAVITEX Extension 69 SLEX 53 Ex10 C6 north section 70 Skyway 54 Ex17 Tarlak Center 71 CAVITEX 55 Ex19 NLEX Phase3 72 Ex23 NLEX-SLEX Connector 56 Ex21 2nd Pan Philippine HW 73 Ex15 CALA Expressway 57 Ex18 Plaridel Bypass 74 Ex1 SEG 9&10 58 Ex20 CLEX 75 Ex4,5 Skyway3 59 Ex12 DIKE Road 76 Source: JICA Project Team

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Table 5.10: Link Type (USERFLAG5) for Rail Link

Link Type - Description Code Link Type - Description Code Transfer Link 90 M-2 Pasig 105 LRT-1 91 M-1 Ortigas 106 LRT-2 92 NSCR North South Commuter 107 MRT-3 93 LRT1-3 LRT-1 North 108 MRT-7 95 LRT2-3 LRT-2 West 109 PNR 98 MRT7-1,2 MRT7-Ex 110 LRT1-2 LRT-1 CAVITE 99 MRT3-1 MRT-3 South 113 M-5 ALABANG 100 M-4 Marikina Mono 114 M-6 CAVITE 101 PNRC-2 PNRC North Extension 115 MRT3-2 MRT-3 Malolos 102 PNRC-3 PNRC South Extension 116 LRT2-2 LRT-2 Ext2 103 MRT-NS-1,2 EDSubway AA-4 117 MRT-NS-1 C5Line 104 Source: JICA Project Team 3) Transit Data The transit network data was initially created using the STRADA transit network (*.TNT) format. However, data conversion was done in order to export the data into the Cube Transportation Modeling Software. The data includes the city bus, jeepney, and the rail route in Mega Manila.

Figure 5.8: Transit Data

Bus Jeepney Rail Source: JICA Project Team

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5.4 Trip Generation Model The trip generation and attraction models for five trip purposes are shown in Table 5.11. Table 5.11: Trip Generation and Attraction Models

Purpose Formula R2 Generation = 0.3063 x [Population>4 years old:Night] + 1124.83 0.90 1. To Work Attraction = 0.7539 x [Secondary Worker:Day] + 0.9288 x [Tertiary:Day] + 630.78 0.78 Generation = 1.2885 x [Elementary:Night] + 0.6961 x [High School/Univ.:Night] + 1046.67 0.95 2. To School Attraction = 1.0269 x [Elementary:Night] + 1.1197 x [High School/Univ.:Night] + 824.10 0.95 3. Business Generation = 0.2906 x [Primary Worker:Night] + 0.1561 x [Secondary+Tertiary:Night] 0.72 + 33837.62 x Dummy + 1506.73 Attraction = 0.2579 x [Primary Worker:Day] + 0.2006 x [Secondary+Tertiary:Day] 0.70 + 27967.75 x Dummy + 776.99 4. Private Generation = 0.2001 x [Population>4 years old:Night] 0.80 + 0.0435 x [Population>4 years old:Day] + 1986.04 Attraction = 0.2891 x [Primary+Secondary+Tertiary:Day] + 0.4866 x [Student:Day] 0.73 + 45019.16 x Dummy + 1543.98 5. To Home Generation = 1.5509 x [Primary+Secondary+Tertiary:Day] + 0.7956 x [Elementary:Day] 0.84 + 1.6794 x [High School/Univ.:Day] + 4339.60 Attraction = 0.8911 x [Population>4 years old:Night] + 3868.03 0.95 Source: JICA Project Team

5.5 Trip Distribution Model The Trip Distribution Model is the Fratar Method. This method assumes that the trip- making pattern will remain the same in the future as it is in the base year. Also, the volume will increase according to the growth in the generating and attracting zones. Future trip ends are computed using the following formula:

n t P A  ik ′ =⋅i ⋅j ⋅ k=1 ttij ij n paij Ak tik k=1 ak

The Fratar Method requires the base year OD table and the future trip ends. The future trip ends will be generated from the Trip Generation Model and since the total generation and attraction values will be different, balancing will be done.

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5.6 Modal Split Model The Modal Split Model is created for car-owning and non-car-owning households. The basic policies of modal split model are follows: (i) The adopted modal split ratio for intra-zone is the present ratio. Intra-zone trips are not affected by the highway assignment results, and (ii) Modal split model parameters are set by purpose and car ownership/non-car ownership; and (iii) Modal split model style between “private” and “public” modes follows that of MMUTIS. Meanwhile, the basic steps of modal split model are shown in Table 5.12 and below. (i) “Truck” trips are estimated by present volume x increase ratio of GRDP/capita; (ii) “Walk” trips, “Other Land” trips, and “Other” trips also adopted the present ratio. (“Other Land” trips are motorized trips, and “Other” trips are non-motorized trips.) (iii) Modal split model between “private” and “public” modes is obtained from the remaining trips after steps (i) and (ii). Table 5.12: Modal Split Model Mode Formula 1. Truck Trip = [Present Volume] x [Increase Ratio of GRDP/Capita] 2. Walk Other Land Transportation Present Modal Split Ratio Other 1 P= 1+Exp(αΔt+ βΔC+ γ) 3. Private Mode Where, Δt: Travel time differences in minutes (private mode – public mode) ΔC: Travel time differences in PHP (private mode – public mode) α, β, γ: Parameters in Table 5.13 Public Mode Remaining Trips Source: JICA Project Team Table 5.13: Modal Split Parameters between Private and Public Modes

Type Purpose α β γ To Work −0.7596 −0.0341 −0.7499 To School −0.4930 −0.0312 −0.2468 1. Car-owing HHs To Business −0.6120 −0.0399 −0.1511 Private −0.0868 −0.0098 −0.5184 To Home −0.6840 −0.0337 −0.8248 To Work −0.2765 −0.0184 −0.1975 To School −0.4930 −0.0312 −0.2468 2. Non-car-owning To Business −0.6120 −0.0399 −0.1511 HHs Private −0.0868 −0.0098 −0.5184 To Home −0.1903 −0.0217 −0.4856 Source: JICA Project Team

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5.7 Highway Assignment Travel speed is decided based on the QV function shown below. This is defined as a result of model validation. Figure 5.9 QV Function

Source: JICA Project Team 5.8 Origin–Destination (OD) Data The base year OD table was prepared based on the results of the Household Interview Survey, while the OD in 2025 and 2035 were estimated using the MUCEP demand forecast model. The estimated total trips by mode are shown in the table below. The OD tables are available in the MUCEP Database. Table 5.14: Total Trips by Mode

Year Walk Private Mode Public Mode Truck Other 2014 10,910,100 6,467,516 11,092,775 275,327 7,189,171 2025 12,517,837 7,092,241 11,293,851 393,450 6,800,664 2035 13,764,329 8,748,371 12,091,295 581,391 7,473,246 Source: JICA Project Team

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5.9 Highway Assignment Result Highway assignment results for 2014 are shown in Figure 5.10. Figure 5.10: Highway Assignment Results for 2014

Source: JICA Project Team

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6 SKETCH PLANNING

6.1 Methodology One of the major constraints in medium to large-size cities is the capacity to undertake travel demand analysis on a regular basis as part of a urban transportation master plan development, implementation, monitoring, and evaluation. The major activity in such efforts is the conduct of travel demand estimation. Up to now, estimation of urban travel demand in medium and large-size cities in the Philippines has been very limited. And the prevailing mindset among planners and decision-makers is that such activities are very costly. It is argued that the development of simplified travel demand estimation techniques has been the subject of research work for a long time now, and best practices and traffic modeling tools are now readily accessible to cities. A feasible approach to simplified transportation demand estimation is the development of sketch planning tools. Sketch planning is the preliminary screening of possible configurations or concepts. Sketch planning modeling aims to realize highlighted objectives based on simplified processes, released parameters estimation, and using data sets at rougher level or with coarser resolution. In comparison with a full-scale model, it can offer such merits as quick response, ease of use and understanding, and low-cost development. The key idea of sketch planning method is to facilitate the generation of alternatives quickly and easily. The main features of the sketch planning methodology include the following: (i) Adopting the logic structure of the traditional transportation modeling process; (ii) Limiting the classification of trip purposes (working, schooling, shopping, and others) and trip modes (private car, transit, and walking); (iii) Setting the appropriate zoning system (grouping of residents and activities that are consistent with past zoning systems); (iv) Updating network representation with appropriate level of aggregation; (v) Utilizing past OD tables as bases for OD table updating; and (vi) Calibrating modest models but where practicable, employing extensive use of matrix estimation techniques. Sketch planning in the context of urban transportation planning is seen as a relatively low-cost, rapid planning exercise, employing short-cut methods, and suited to circumstances where quick responses are often required to tackle complex urban transportation problems. Such circumstances are typically characterized by limited or invalid local data with which to formulate an effective and efficient response, obliging one to rely on proxy data collected from similar settlements in the same region, country, or region. Where primary data is not available, sketch-plan methodologies can rely on traffic generation and production relationships derived from former studies of settlements of similar characteristics. These are used to limit data collection and expedite the execution of sketch-plan exercises. In instances, however, where OD traffic surveys have been conducted in the past, the

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use of low-cost methods of updating trip patterns in travel demand forecasting is especially appropriate. The principal steps of the sketch-plan methodology are: (a) Step 1: This entails an assessment and review of existing conditions which concern (i) current national, provincial, and urban transportation and development policies, plans, and projects affecting the study area; (ii) the present characteristics and condition of urban transportation services and facilities; and (iii) selected priority areas of concern for which critical data is needed. (b) Step 2: This requires the undertaking of simple urban travel demand analysis and forecasting exercises tempered by normative, enabling, and controlling policies as appropriate. Normative policies or plans are those that provide direction, aspirations, and standards for government, community, and the private sector to pursue and strive after. Enabling policies and plans are designed to support welcome market forces and community preferences which simultaneously contribute to normative directives. Controlling policies and plans are those that provide the basis for enforcement and regulation, particularly of the private sector and communities, to ensure both normative and enabling directives are followed within the prescribed limits. (c) Step 3: This involves the identification of transportation infrastructure and service problems. (d) Step 4: This necessitates the screening of identified urban transportation problems. It involves the categorization and prioritization of problems in terms of spatial characteristics; different professional and vested interests; root problems and their manifestations; and current and future problems impeding important development considerations. (e) Step 5: This entails the preparation of responses to screened problems for citywide and area/corridor/street-specific situations under selected policy circumstances. (f) Step 6: This requires the evaluation and appraisal of urban transportation proposals. Firstly, a proposal’s contribution to national, provincial, and local development objectives is assessed together with its compatibility to available resources. Secondly, it will be assessed in terms of more conventional optimization terms. (g) Step 7: This involves the integration and coordination of proposals generated by the planning approach. The above-mentioned steps are not in any way strictly sequential but allow forward and backward feedback. There is a need to develop clear guidelines, standards, and toolkits on the sketch-plan methodology in urban transportation planning for medium to large-size cities in the country. These guidelines and standards should be integrated with existing statutory guidelines and standards in land use planning, local development planning, and existing engineering standards for the built environment. 6.2 Sample Sketch Planning Model A sketch planning model was developed for General Santos City, a regional city located in Mindanao, in order to assess the existing and future urban transportation situation in the city. It also provides the basis for evaluating the transportation impacts of the

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proposed redevelopment of the city’s Central Public Market (CPM) and Integrated Food Terminal (IFT). The sketch planning model is structured as a travel demand forecasting model but based on simplified processes and released parameters estimation, and using data sets at rougher levels or with coarser resolutions. The model made extensive use of available road inventory data, existing OD tables, and existing traffic. The development of the model consists of the following steps, namely: (i) preparation of road network model; (ii) preparation of zoning system; (iii) preparation of OD tables; (iv) OD matrix estimation; and (v) traffic assignment.

Figure 6.1: Sketch Planning Model Flow

Road Inventory OD Matrix GIS Data Data Calibration

Preparation of Preparation of Preparation of Road Network Origin-Destination Zoning System Model (OD) Tables

Traffic Forecasting Model

Traffic Assignment

Traffic Forecasts

Source: JICA Project Team The zoning system for General Santos City was based on its existing boundaries. It consists of 26 internal zones and four external zones. Table 6.1: Description of Zoning System for General Santos City 2011 2011 TAZ Zone Name Land Area Population TAZ Zone Name Land Area Population 1 Dadiangas North 95.09 8,567 14 Katanggawan 1,958.39 12,138 2 Dadiangas East 61.07 4,161 15 Ligaya 651.56 4,006 3 Dadiangas South 61.68 6,955 16 Baluan 1,059.33 7,349 4 Dadiangas West 86.29 14,063 17 Buayan 474.03 9,950 5 City Heights 480.62 18,757 18 Siguel 6,051.67 10,880 6 San Isidro 1,481.65 39,369 19 San Jose 5,969.05 9,220 7 Lagao 1,347.95 49,252 20 Sinawal 6,176.92 11,278 8 Bula 300.94 29,943 21 Mabuhay 4,994.70 22,205 9 Labangal 1,285.03 57,424 22 Conel 5,670.74 10,288 10 Calumpang 654.03 68,524 23 Olympog 2,506.75 3,113 11 Tambler 4,386.05 18,505 24 Upper Labay 2,623.96 2,838 12 Fatima 2,469.05 61,221 25 Tinagacan 2,121.80 5,952 13 Apopong 2,032.91 39,896 26 Batomelong 1,454.50 3,128 Source: JICA Project Team

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Figure 6.2: Traffic Analysis Zones in General Santos City

Source: JICA Project Team

The road network of the model consists of nodes and links. Each of the links represents a section of the road and each of the nodes represents an intersection. The elements used in a link are length, maximum speed, capacity, fare system, directional regulation, and volume-speed relationship. Links are classified to determine capacity, maximum speed, and volume-speed relationship.

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Table 6.2: Length of Roads in General Santos City by Barangay

Total Length Length by Surface Type (km) Barangay (km) Asphalt Gravel Earth Concrete Apopong 7.24 - - 4.34 2.9 Baluan 20.585 - - 11.795 8.79 Batomelong 6.261 - 2.4 1.695 2.166 Bawing 23.905 - 23.473 - 0.432 Buayan 19.795 1.05 0.51 16.18 2.055 Bula 17.345 - - 7.345 10 Calumpang 23.628 - - 7.588 16.04 City Heights 14.027 1.532 - 5.845 6.65 Conel 21.25 - - 14.465 6.785 Dadiangas East 9.15 - - 0.05 9.1 Dadiangas North 12.026 1.022 - - 11.004 Dadiangas South 11.315 1.388 - - 9.927 Dadiangas West 7.437 0.646 - 0.266 6.525 Fatima 91.038 - - 80.784 10.254 Government Center 1.683 0.306 - - 1.377 Katangawan 42.691 0.22 0.37 35.791 6.311 Labangal 9.938 - - 9.54 0.398 Lagao 38.99 3.973 - 17.257 17.759 Ligaya 11.998 - - 10.892 1.106 Mabuhay 37.753 - - 34.028 3.725 Olympog 6.916 - - 6.174 0.742 San Isidro 31.11 0.606 - 23.515 6.989 San Jose 27.75 - - 23.75 4 Sinawal 27.346 - - 23.4 3.946 Tambler 2.687 - - 0.458 2.229 Tinagakan 19.46 - - 15.785 3.675 Upper Labay 39.87 - - 37.52 2.35 Grand Total 583.194 10.743 26.753 388.463 157.235 Source: City Engineer’s Office of Gen. Santos Figure 6.3: Road Network Data of General Santos City

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The maximum speed was set according to the class of roads, as follows:

• National highway : 60 km/h • Major urban road : 50 km/h • Secondary urban road : 50 km/h • Barangay road : 40 km/h The lane capacity of each class of road is set as follows:

• Expressway : 1,800 PCU/h/lane • Major urban road : 1,600 PCU/h/lane • Secondary urban road : 1,600 PCU/h/lane • Barangay road : 1,400 PCU/h/lane Traffic volumes by vehicle type were multiplied by their respective passenger car equivalent factors (PCEFs) in order to establish the traffic volumes in terms of passenger car unit (PCU). Travel time changes due to congestion, that is, the bigger the traffic volume, the longer the traffic time on the link. The model for General Santos City incorporated such speed reduction by traffic volume as a link cost function, which represents volume-speed relationship. Table 6.3: Passenger Car Equivalent Factors

Vehicle Type PCEF Passenger Car/Van/AUV 1.0 Public Utility Jeepney (PUJ) 1.5 Public Utility Bus (PUB) 2.2 Medium Truck 2.0 Large Truck 2.5 Tricycle 0.8 Motorcycle 0.5 Source: JICA Project Team

Figure 6.4: Volume-Speed Relationship

Speed

V

V x 0.1 Volume 30% Capacity Capacity

Source: JICA Project Team

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Traffic count data along national roads are available due to the DPWH Road Traffic Information Application (RTIA). As such, annual average daily traffic (AADT) volumes along sections of the national highway in General Santos City were utilized as screen line data. Traffic growth rate (TGR) data are also available from the historical data in the DPWH RTIA. The recorded 3.401% growth for passenger cars in South Cotabato is the highest in the region and also one of the highest in the country. Table 6.4: Traffic Volume along National Highways in General Santos City Truck Truck Rigid Rigid Truck Truck Motor - PassengPassenger Goods Small Large Semi- Semi- Road Name Truck Truck Trailers Trailers Total Tricycle er Car Utility Utility Bus Bus Trailer Trailer 2 Axles 3+ Axles 4 Axles 5+ Axles 3&4 Axles 5+ Axles Digos–Makar 13,37 Road 13,406 2 2,946 1,888 23 294 1,391 438 91 121 0 1 33,971 Makar–Marbel Road 7,813 5,727 1,045 406 16 20 1,043 443 109 213 0 0 16,835 Jct Digos–Buayan 8,427 1,568 672 985 9 9 387 69 18 17 0 0 12,161 Airport Road Makar–Kiamba 19,585 5,377 1,332 529 19 32 2,165 325 84 96 12 0 29,556 Road Source: DPWH

Table 6.5: Traffic Growth Rate in Region XII Truck Rigid Rigid Truck Semi- Truck Truck Motor - Passenger Passenger Goods Large Semi- Region/ Province Small Bus Truck Truck Trailer Trailers Trailers Tricycle Car Utility Utility Bus Trailer 3&4 Axles 4 Axles 5+ Axles 2 Axles 3+ Axles 5+ Axles REGION XII 2.497 3.047 2.497 2.407 2.497 2.497 2.407 2.407 2.407 2.407 2.407 2.407 South Cotabato 2.648 3.401 2.648 2.525 2.648 2.648 2.525 2.525 2.525 2.525 2.525 2.525 Sarangani 2.371 2.753 2.371 2.309 2.371 2.371 2.309 2.309 2.309 2.309 2.309 2.309 Sultan Kudarat 2.391 2.799 2.391 2.324 2.391 2.391 2.324 2.324 2.324 2.324 2.324 2.324 North Cotabato 2.417 2.961 2.417 2.345 2.417 2.417 2.345 2.345 2.345 2.345 2.345 2.345 Cotabato City 2.632 3.362 2.632 2.512 2.632 2.632 2.512 2.512 2.512 2.512 2.512 2.512 Source: DPWH

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Figure 6.5: Incremental Traffic Assignment

Start Traffic volume on each link was calculated by allocating every OD data to minimum routes for each OD pair. In order to forecast traffic volumes, Set Increment Count C=1 the highway network was loaded using vehicle trips in passenger car units or PCU. OD Data

Calculate travel time of links

Search minimum route

Assign 1/N of OD trips to links

C=C+1

No C>N?

Yes

End

Source: JICA Project Team

The trip generation stage involved the preparation of a database of zonal characteristics including total population, number of elementary students (STUDELEM), number of high school students (STUDHS), number of college students (STUDCOLL), number of workers in the primary sector (EMPPRI), number of workers in the secondary sector (EMPSEC), and number of workers in the tertiary sector (EMPTER).

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Figure 6.6: Zonal Data

Under a sketch planning approach, the parameters of the trip generation and trip distribution model can be transferred from previous work on cities with similar characteristics. The parameters and structure of the trip generation and attraction model used for General Santos City were adopted from a previous study of Davao City1. Figures 6.7 and 6.8 present the trip production and trip attraction equations, respectively.

1 In 1979, the then Ministry of Public Works and Highways (MPWH) set up a team for a Davao City Urban Transport Cum Land Use Study (DCUTCLUS) and a steering committee consisting of representatives from concerned agencies.

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Figure 6.7: Trip Production Equations ; purpose = home based P[1] = (hbp_e*(zi.1.EMPSEC+zi.1.EMPTER) + hbp_sc*zi.1.TOTALSTUD - 728) ; purpose = non-home based P[2] = (nhbp_e*(zi.1.EMPSEC+zi.1.EMPTER) + 134) ; purpose = school P[3] = (schp_sc*zi.1.TOTALSTUD + 11)

hbp_e = 1.0940 ; production trip rate per secondary and tertiary employee per day hbp_sc = 1.2542 ; production trip rate per pupil/student per day nhbp_e = 0.6648 ; production trip rate per secondary and tertiary employee per day schp_sc = 0.9904 ; production trip rate per pupil/student per day hbp_sc = 1.254 ; production trip rate per pupil/student per day nhbp_e = 0.6648 ; production trip rate per secondary and tertiary employee per day schp_sc = 0.9904 ; production trip rate per pupil/student per day Source: JICA Project Team Figure 6.8: Trip Attraction Equations ; purpose = home based A[1] = (hba_p*zi.1.POP2009 - 438) ; purpose = non-home based A[2] = (nhba_e*(zi.1.EMPSEC+zi.1.EMPTER) - 163) ; purpose = school A[3] = (scha_sc*zi.1.TOTALSTUD - 24)

hba_p = 0.6713 ; attraction trip rate per person (population) per day nhba_e = 0.8223 ; attraction trip rate per secondary and tertiary employee per day scha_sc = 1.0030 ; attraction trip rate per pupil/student per day hba_p = 0.6713 ; attraction trip rate per person (population) per day nhba_e = 0.8223 ; attraction trip rate per secondary and tertiary employee per day scha_sc = 1.0030 ; attraction trip rate per pupil/student per day Source: JICA Project Team

After the trip generation process, a trip distribution process was performed. The trip distribution model was also patterned after DCUTCLUS. The result of the trip distribution process is an initial base year OD table of person-trips. The form of the trip distribution model is: AT⋅ −γ =⋅⋅ ij ij XBGij ij i n ⋅ −γ  ATij ij j =1 ()ji≠ where Xij is the trips between zones i and j

Gi is the generated trips of zone i

Aj is the attracted trips of zone j

Tij is the distance between zones i and j

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γis a parameter

Bij is a coefficient of access which expresses the intensity of zone linkage

For the analysis, the parameters γ and Bij were considered to have a value of 1. The matrix estimation component produces calibrated OD matrices based on existing traffic count data along screen lines including assumptions of confidence levels of total trip values. This component utilizes the Matrix Analyst module of the Cube transportation modeling software. Using the initial base year matrix, initial base year OD matrices by mode were generated using the assumed mode share values shown below. Figure 6.9 presents the Matrix Calibration application in the model environment. (i) Mode share of car trips – 21%; (ii) Mode share of PUJ trips - 2%; (iii) Mode share of PUB trips - 2%; (iv) Mode Share of Truck Trips - 5%; M (v) Mode Share of Motorcycle Trips - 40%; (vi) Mode Share of Tricycle Trips - 30%.

Figure 6.9: Matrix Calibration Application

Source: JICA Project Team

Separate matrix estimation steps were performed for each of the vehicle classes. Figure 6.10 presents the separate matrix estimation step for cars. Similar steps were performed separately for PUJs, PUBs, trucks, motorcycles, and tricycles. The end results of the matrix calibration step were calibrated OD matrices by mode.

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Figure 6.10: Matrix Calibration for Car Trips

Source: JICA Project Team Figure 6.11: Calibrated OD Matrices by Mode

Source: JICA Project Team

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The Highway Assignment component performs traffic assignment procedures to generate link volumes on the network. Separate assignment steps were performed for daily and peak-hour traffic volumes. Analysis of daily traffic is often used for long-term planning, while analysis of peak-hour traffic demand provides the basis for operational improvements on the network. Figure 6.12: Highway Assignment Application

Source: JICA Project Team

Figure 6.13: Link Traffic Volumes Figure 6.14: Link Traffic Volumes for Daily Traffic for Peak-Hour Traffic

Source: JICA Project Team Source: JICA Project Team

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Skim data are useful in evaluating the situation on the road network. Under the model environment, zone-to-zone skim data for travel time, distance, and speed are generated automatically in the form of tables. Figure 6.15: Daily Time, Distance, and Speed Skims

Source: JICA Project Team Figure 6.16: Peak-Hour Time, Distance, and Speed Skims

Source: JICA Project Team

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As a typical output, the system can present a map showing the desire lines for the city. The thickness of the band represents the magnitude of OD trips. It is worthwhile to note that the sketch planning model developed thus far can be enhanced into a full-blown traffic forecasting model for General Santos City. Figure 6.17: Desire Lines for General Santos City

Source: JICA Project Team

6-15

ANNEXES

APPENDIX A: DESCRIPTION OF THE ZONING SYSTEM Table A-1: Description of Zoning System MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 1 Inside NCR METRO_MANILA Manila Divisoria/Zaragosa 1 1 1 2 Inside NCR METRO_MANILA Manila Tondo/Moriones 1 1 1 3 Inside NCR METRO_MANILA Manila Tondo/Herbosa 1 1 1 4 Inside NCR METRO_MANILA Manila Tondo/H.Lopez 1 1 1 5 Inside NCR METRO_MANILA Manila Tondo/J.Luna 1 1 1 6 Inside NCR METRO_MANILA Manila Tondo/Corregidor 1 1 1 7 Inside NCR METRO_MANILA Manila La Loma/Chinese Cemetery 1 1 2 8 Inside NCR METRO_MANILA Manila Tondo/J.A.Santos 1 1 1 9 Inside NCR METRO_MANILA Manila Sta.Cruz/J.A.Santos 1 1 1 10 Inside NCR METRO_MANILA Manila Divisoria/Del Pan 1 1 2 11 Inside NCR METRO_MANILA Manila Binondo/J.Luna 1 1 2 12 Inside NCR METRO_MANILA Manila Binondo/Reina Regente 1 1 2 13 Inside NCR METRO_MANILA Manila Binondo/Mesericordia 1 1 2 14 Inside NCR METRO_MANILA Manila Quiapo/Carriedo 1 1 2 15 Inside NCR METRO_MANILA Manila Sta.Cruz/D.Jose 1 1 2 16 Inside NCR METRO_MANILA Manila Sta.Crus/Bambang 1 1 2 17 Inside NCR METRO_MANILA Manila Sta.Cruz/San Lazaro 1 1 2 18 Inside NCR METRO_MANILA Manila Quiapo/Globo de Oro 1 1 2 19 Inside NCR METRO_MANILA Manila Quiapo/Bilibid Viejo 1 1 2 20 Inside NCR METRO_MANILA Manila Sampaloc/FEU/UE 1 1 3 21 Inside NCR METRO_MANILA Manila Sta.Mesa/Lardizabal Ext. 1 1 3 22 Inside NCR METRO_MANILA Manila Sta.Mesa/Peereza Ext. 1 1 3 23 Inside NCR METRO_MANILA Manila Sampaloc/NU 1 1 3 24 Inside NCR METRO_MANILA Manila Sampaloc/UST 1 1 3 25 Inside NCR METRO_MANILA Manila Sampaloc/Florentino 1 1 3 26 Inside NCR METRO_MANILA Manila Sampaloc/Calamba 1 1 3 27 Inside NCR METRO_MANILA Manila Sampaloc/S.Loyola 1 1 3 28 Inside NCR METRO_MANILA Manila Sta.Mesa/Altura Ext. 1 1 3 29 Inside NCR METRO_MANILA Manila Old Sta.Mesa/V.Mapa 1 1 3 30 Inside NCR METRO_MANILA Manila Sta.Mesa/P.Sanchez 1 1 3 31 Inside NCR METRO_MANILA Manila Punta 1 1 3 32 Inside NCR METRO_MANILA Manila Sta.Mesa/R.Magsaysay 1 1 3 33 Inside NCR METRO_MANILA Manila San Miguel/J.P.Laurel 1 1 3 34 Inside NCR METRO_MANILA Manila Quiapo/C.Palanca 1 1 3 35 Inside NCR METRO_MANILA Manila South Port Area 1 1 4 36 Inside NCR METRO_MANILA Manila Intramuros/Muralla 1 1 4 37 Inside NCR METRO_MANILA Manila Intramuros/Arroceros 1 1 4 38 Inside NCR METRO_MANILA Manila Intramuros/Tanque 1 1 4 39 Inside NCR METRO_MANILA Manila Ermita 1 1 4 40 Inside NCR METRO_MANILA Manila Paco/Apacible 1 1 4 41 Inside NCR METRO_MANILA Manila Paco/Canociga 1 1 4 42 Inside NCR METRO_MANILA Manila Paco/Linao (Dart) 1 1 4 43 Inside NCR METRO_MANILA Manila Malate/PCU 1 1 4 44 Inside NCR METRO_MANILA Manila Malate/J.C.Bocobo 1 1 4 45 Inside NCR METRO_MANILA Manila Malate/Harrison Plaza 1 1 4 46 Inside NCR METRO_MANILA Manila San Andres/L.Guinto 1 1 4 47 Inside NCR METRO_MANILA Manila San Andres/SSH 1 1 4 48 Inside NCR METRO_MANILA Manila San Andres/Diamante 1 1 4 49 Inside NCR METRO_MANILA Manila Paco/Fabie 1 1 4 50 Inside NCR METRO_MANILA Manila Sta.Ana/Estrada 1 1 4 51 Inside NCR METRO_MANILA Manila San Miguel/Malacanang 1 1 4 52 Inside NCR METRO_MANILA Manila Pandacan/Beata 1 1 4 53 Inside NCR METRO_MANILA Manila Pandacan/T.Claudio 1 1 4 54 Inside NCR METRO_MANILA Manila Sta.Ana/Panaderos 1 1 4 55 Inside NCR METRO_MANILA Manila Manila Noth Harbour 1 1 1 56 Inside NCR METRO_MANILA Manila MICT 1 1 1 57 Inside NCR METRO_MANILA Manila BASECO 1 1 4 58 Inside NCR METRO_MANILA Pasay_City San Jose 2 1 5 59 Inside NCR METRO_MANILA Pasay_City San Isidro 2 1 5 60 Inside NCR METRO_MANILA Pasay_City Sta.Clara/Leveriza 2 1 5 61 Inside NCR METRO_MANILA Pasay_City Sta.Clara/Tramo 2 1 5 62 Inside NCR METRO_MANILA Pasay_City San Rafael 2 1 5 63 Inside NCR METRO_MANILA Pasay_City San Roque 2 1 5 64 Inside NCR METRO_MANILA Pasay_City Tabon 2 1 5 65 Inside NCR METRO_MANILA Pasay_City Malibay 2 1 5 66 Inside NCR METRO_MANILA Pasay_City Maricaban 2 1 5 67 Inside NCR METRO_MANILA Pasay_City Sto.Nino(Pasay) 2 1 5

A-1

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 68 Inside NCR METRO_MANILA Pasay_City Villamore Air Base 2 1 5 69 Inside NCR METRO_MANILA Pasay_City Air Cargo 2 1 5 70 Inside NCR METRO_MANILA Pasay_City Domestic Airport 2 1 5 71 Inside NCR METRO_MANILA Pasay_City PICC(reclamation area) 2 1 5 72 Inside NCR METRO_MANILA Pasay_City CITE(reclamation area) 2 1 5 73 Inside NCR METRO_MANILA Makati_City Bangkal 3 1 6 74 Inside NCR METRO_MANILA Makati_City Palanan 3 1 6 75 Inside NCR METRO_MANILA Makati_City Pio Del Pilar 3 1 6 76 Inside NCR METRO_MANILA Makati_City Tejeros 3 1 6 77 Inside NCR METRO_MANILA Makati_City Olympia 3 1 6 78 Inside NCR METRO_MANILA Makati_City Poblacion(Makati) 3 1 6 79 Inside NCR METRO_MANILA Makati_City Legaspi Village 3 1 6 80 Inside NCR METRO_MANILA Makati_City San Lorenzo 3 1 6 81 Inside NCR METRO_MANILA Makati_City Ayala Center 3 1 6 82 Inside NCR METRO_MANILA Makati_City Salcedo Village 3 1 6 83 Inside NCR METRO_MANILA Makati_City Bel-Air II 3 1 6 84 Inside NCR METRO_MANILA Makati_City Urdaneta 3 1 6 85 Inside NCR METRO_MANILA Makati_City Bel-Air I 3 1 6 86 Inside NCR METRO_MANILA Makati_City Guadalupe Viejo 3 1 6 87 Inside NCR METRO_MANILA Makati_City Guadalupe Nuevo 3 1 6 88 Inside NCR METRO_MANILA Makati_City Cembo 3 1 6 89 Inside NCR METRO_MANILA Makati_City Post Proper Northside 3 1 6 90 Inside NCR METRO_MANILA Makati_City Rembo 3 1 6 91 Inside NCR METRO_MANILA Makati_City Pembo 3 1 6 92 Inside NCR METRO_MANILA Taguig_City Fort Bonifacio 4 1 7 93 Inside NCR METRO_MANILA Taguig_City Pinagsama 4 1 7 94 Inside NCR METRO_MANILA Makati_City Dasmarinas/Forbs 3 1 6 95 Inside NCR METRO_MANILA Makati_City Magallanes 3 1 6 96 Inside NCR METRO_MANILA Mandaluyong_City Plainview 5 1 8 97 Inside NCR METRO_MANILA Mandaluyong_City Old Zaniga 5 1 8 98 Inside NCR METRO_MANILA Mandaluyong_City Poblacion(Mandaluyong) 5 1 8 99 Inside NCR METRO_MANILA Mandaluyong_City Hagdang Bato 5 1 8 100 Inside NCR METRO_MANILA Mandaluyong_City Addition Hills 5 1 8 101 Inside NCR METRO_MANILA Mandaluyong_City Barangka 5 1 8 102 Inside NCR METRO_MANILA Mandaluyong_City Highway Hills 5 1 8 103 Inside NCR METRO_MANILA Mandaluyong_City Wack-Wack/Greenhills 5 1 8 104 Inside NCR METRO_MANILA Mandaluyong_City Ortigas Center 5 1 8 105 Inside NCR METRO_MANILA San_Juan East Greenhills 6 1 9 106 Inside NCR METRO_MANILA San_Juan Greenhills Com'l Center 6 1 9 107 Inside NCR METRO_MANILA San_Juan West Crame 6 1 9 108 Inside NCR METRO_MANILA San_Juan Batis 6 1 9 109 Inside NCR METRO_MANILA San_Juan Corazon De Jesus 6 1 9 110 Inside NCR METRO_MANILA Quezon_City Dona Imelda 7 1 10 111 Inside NCR METRO_MANILA Quezon_City Santo Nino 7 1 10 112 Inside NCR METRO_MANILA Quezon_City Tatalon 7 1 10 113 Inside NCR METRO_MANILA Quezon_City Santa Teresita 7 1 11 114 Inside NCR METRO_MANILA Quezon_City N.S.Amoranto(Gintong Silahis) 7 1 11 115 Inside NCR METRO_MANILA Quezon_City Manresa 7 1 11 116 Inside NCR METRO_MANILA Quezon_City Balingasa 7 1 11 117 Inside NCR METRO_MANILA Quezon_City Apolonio Samson 7 1 11 118 Inside NCR METRO_MANILA Quezon_City Masambong 7 1 11 119 Inside NCR METRO_MANILA Quezon_City Santo Domingo(Matalahib) 7 1 11 120 Inside NCR METRO_MANILA Quezon_City Del Monte 7 1 11 121 Inside NCR METRO_MANILA Quezon_City San Antonio 7 1 11 122 Inside NCR METRO_MANILA Quezon_City Veterans Village 7 1 11 123 Inside NCR METRO_MANILA Quezon_City Phil-Am7 111 124 Inside NCR METRO_MANILA Quezon_City South Triangle 7 1 10 125 Inside NCR METRO_MANILA Quezon_City Kamuning 7 1 10 126 Inside NCR METRO_MANILA Quezon_City Roxas 7 1 10 127 Inside NCR METRO_MANILA Quezon_City Kalusugan 7 1 10 128 Inside NCR METRO_MANILA Quezon_City Mariana 7 1 10 129 Inside NCR METRO_MANILA Quezon_City Kaunlaran 7 1 10 130 Inside NCR METRO_MANILA Quezon_City Immaculate Concepcion 7 1 10 131 Inside NCR METRO_MANILA Quezon_City Bagong Lipunan Crame 7 1 10 132 Inside NCR METRO_MANILA Quezon_City Crame 7 1 10 133 Inside NCR METRO_MANILA Quezon_City Ugong Norte 7 1 12 134 Inside NCR METRO_MANILA Quezon_City Camp Aguinaldo 7 1 12 135 Inside NCR METRO_MANILA Quezon_City White Plains 7 1 12 136 Inside NCR METRO_MANILA Quezon_City Murphy District 7 1 12 137 Inside NCR METRO_MANILA Quezon_City Cubao(Araneta Center) 7 1 12

A-2

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 138 Inside NCR METRO_MANILA Quezon_City E. Rodriguez 7 1 12 139 Inside NCR METRO_MANILA Quezon_City San Roque 7 1 12 140 Inside NCR METRO_MANILA Quezon_City Escopa 7 1 12 141 Inside NCR METRO_MANILA Quezon_City Quirino 3 7 1 12 142 Inside NCR METRO_MANILA Quezon_City Quirino 2 7 1 12 143 Inside NCR METRO_MANILA Quezon_City Loyola Heights 7 1 13 144 Inside NCR METRO_MANILA Quezon_City Teachers Village 7 1 13 145 Inside NCR METRO_MANILA Quezon_City QMC 7 1 13 146 Inside NCR METRO_MANILA Quezon_City U.P. Campus 7 1 13 147 Inside NCR METRO_MANILA Quezon_City Batasan Hills 7 1 13 148 Inside NCR METRO_MANILA Quezon_City Matandang Balara 7 1 13 149 Inside NCR METRO_MANILA Quezon_City Holy Spirit 7 1 13 150 Inside NCR METRO_MANILA Quezon_City Payatas 7 1 13 151 Inside NCR METRO_MANILA Quezon_City Bagong Silangan 7 1 13 152 Inside NCR METRO_MANILA Quezon_City Constitution Hills 7 1 13 153 Inside NCR METRO_MANILA Quezon_City Commonwealth 7 1 13 154 Inside NCR METRO_MANILA Quezon_City Fairview 7 1 13 155 Inside NCR METRO_MANILA Quezon_City Pasong Putik 7 1 13 156 Inside NCR METRO_MANILA Quezon_City Kaligayahan 7 1 13 157 Inside NCR METRO_MANILA Quezon_City San Agustin 7 1 13 158 Inside NCR METRO_MANILA Quezon_City Gulod 7 1 13 159 Inside NCR METRO_MANILA Quezon_City Sauyo 7 1 13 160 Inside NCR METRO_MANILA Quezon_City Bagbag 7 1 13 161 Inside NCR METRO_MANILA Quezon_City Tandang Sora 7 1 13 162 Inside NCR METRO_MANILA Quezon_City Pasong Tamo 7 1 13 163 Inside NCR METRO_MANILA Quezon_City Culiat 7 1 13 164 Inside NCR METRO_MANILA Quezon_City Project 6 7 1 13 165 Inside NCR METRO_MANILA Quezon_City Ramon Magsaysay 7 1 13 166 Inside NCR METRO_MANILA Quezon_City Bahay Toro 7 1 13 167 Inside NCR METRO_MANILA Quezon_City Baesa 7 1 13 168 Inside NCR METRO_MANILA Quezon_City Sangandaan 7 1 13 169 Inside NCR METRO_MANILA CALOOCAN_CITY Bo. San Jose 8 1 14 170 Inside NCR METRO_MANILA CALOOCAN_CITY West 3/4 Ave. 8 1 14 171 Inside NCR METRO_MANILA CALOOCAN_CITY A.Mabini 8 1 14 172 Inside NCR METRO_MANILA CALOOCAN_CITY Dagat Dagatan 8 1 14 173 Inside NCR METRO_MANILA CALOOCAN_CITY West 8/10 Ave. 8 1 14 174 Inside NCR METRO_MANILA CALOOCAN_CITY Grace Park 8 1 14 175 Inside NCR METRO_MANILA CALOOCAN_CITY Sangandaan 8 1 14 176 Inside NCR METRO_MANILA CALOOCAN_CITY Bagon Barrio EDSA 8 1 14 177 Inside NCR METRO_MANILA CALOOCAN_CITY Bagon Barrio Center 8 1 14 178 Inside NCR METRO_MANILA CALOOCAN_CITY Bagon Barrio East 8 1 14 179 Inside NCR METRO_MANILA CALOOCAN_CITY Bagumbong 1(CN) 8 1 15 180 Inside NCR METRO_MANILA CALOOCAN_CITY Bagumbong 2(CN) 8 1 15 181 Inside NCR METRO_MANILA CALOOCAN_CITY Bagumbong 3(CN) 8 1 15 182 Inside NCR METRO_MANILA CALOOCAN_CITY Camarin 1(CN) 8 1 15 183 Inside NCR METRO_MANILA CALOOCAN_CITY Camarin 2(CN) 8 1 15 184 Inside NCR METRO_MANILA CALOOCAN_CITY North 1(CN) 8 1 15 185 Inside NCR METRO_MANILA CALOOCAN_CITY West(CN) 8 1 15 186 Inside NCR METRO_MANILA Valenzuela_City Canumay 9 1 16 187 Inside NCR METRO_MANILA Valenzuela_City Mapulang Lupa/Ugong 9 1 16 188 Inside NCR METRO_MANILA Valenzuela_City Bagbaguin 9 1 16 189 Inside NCR METRO_MANILA Valenzuela_City Hen. T. De Leon 9 1 16 190 Inside NCR METRO_MANILA Valenzuela_City Marulas 9 1 16 191 Inside NCR METRO_MANILA Valenzuela_City Karuhatan 9 1 16 192 Inside NCR METRO_MANILA Valenzuela_City Maysan 9 1 16 193 Inside NCR METRO_MANILA Valenzuela_City Malanday(Valenzuela) 9 1 16 194 Inside NCR METRO_MANILA Valenzuela_City Dalandanan 9 1 16 195 Inside NCR METRO_MANILA Malabon_City Maysilo/Panghulo 10 1 17 196 Inside NCR METRO_MANILA Malabon_City Potrero 10 1 17 197 Inside NCR METRO_MANILA Malabon_City Tugatog 10 1 17 198 Inside NCR METRO_MANILA Malabon_City Longos 10 1 17 199 Inside NCR METRO_MANILA Malabon_City Tonsuya 10 1 17 200 Inside NCR METRO_MANILA Malabon_City Baritan/Concepcion 10 1 17 201 Inside NCR METRO_MANILA Malabon_City Dampalit 10 1 17 202 Inside NCR METRO_MANILA Navotas_City Tanza 11 1 18 203 Inside NCR METRO_MANILA Navotas_City Tangos 11 1 18 204 Inside NCR METRO_MANILA Navotas_City San Jose 11 1 18 205 Inside NCR METRO_MANILA Navotas_City Navotas East/West 11 1 18 206 Inside NCR METRO_MANILA Navotas_City North Bay Blvd. 11 1 18 207 Inside NCR METRO_MANILA Navotas City Navotas Fishport 11 1 18

A-3

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 208 Inside NCR METRO_MANILA Marikina_City Nangka 12 1 19 209 Inside NCR METRO_MANILA Marikina_City Parang 12 1 19 210 Inside NCR METRO_MANILA Marikina_City Concepcion(Marikina) 12 1 19 211 Inside NCR METRO_MANILA Marikina_City Marikina Heights 12 1 19 212 Inside NCR METRO_MANILA Marikina_City Calumpang/San Roque 12 1 19 213 Inside NCR METRO_MANILA Marikina_City Santo Nino 12 1 19 214 Inside NCR METRO_MANILA Marikina_City Malanday(Marikina) 12 1 19 215 Inside NCR METRO_MANILA Marikina_City Barangka(Marikina) 12 1 19 216 Inside NCR METRO_MANILA Pasig_City Kalawaan 13 1 20 217 Inside NCR METRO_MANILA Pasig_City Santolan/Manggahan 13 1 20 218 Inside NCR METRO_MANILA Pasig_City Santa Lucia 13 1 20 219 Inside NCR METRO_MANILA Pasig_City Maybunga 13 1 20 220 Inside NCR METRO_MANILA Pasig_City Ugong 13 1 20 221 Inside NCR METRO_MANILA Pasig_City San Antonio 13 1 20 222 Inside NCR METRO_MANILA Pasig_City Kapitolyo 13 1 20 223 Inside NCR METRO_MANILA Pasig_City Bagong Ilog 13 1 20 224 Inside NCR METRO_MANILA Pasig_City Bambang 13 1 20 225 Inside NCR METRO_MANILA Pasig_City Caniogan 13 1 20 226 Inside NCR METRO_MANILA Pasig_City Pinagbuhatan 13 1 20 227 Inside NCR METRO_MANILA Pateros Santa Ana(Pateros) 14 1 21 228 Inside NCR METRO_MANILA Taguig_City Bagumbayan 4 1 7 229 Inside NCR METRO_MANILA Taguig_City Bicutan 4 1 7 230 Inside NCR METRO_MANILA Taguig_City Signal Village 4 1 7 231 Inside NCR METRO_MANILA Taguig_City Western Bicutan 4 1 7 232 Inside NCR METRO_MANILA Taguig_City Hagonoy 4 1 7 233 Inside NCR METRO_MANILA Taguig_City Ususan 4 1 7 234 Inside NCR METRO_MANILA Parañaque City Baclaran 15 1 22 235 Inside NCR METRO_MANILA Parañaque CityTambo 15 1 22 236 Inside NCR METRO_MANILA Parañaque City La Huerta 15 1 22 237 Inside NCR METRO_MANILA Parañaque City San Dionisio 15 1 22 238 Inside NCR METRO_MANILA Parañaque CityMoonwalk 15 1 22 239 Inside NCR METRO_MANILA Parañaque City Santo Nino(Paranaque) 15 1 22 240 Inside NCR METRO_MANILA Parañaque CityMerville 15 1 22 241 Inside NCR METRO_MANILA Parañaque City Sun Valley 15 1 22 242 Inside NCR METRO_MANILA Parañaque City Don Bosco 15 1 22 243 Inside NCR METRO_MANILA Parañaque City Marcelo Green Village 15 1 22 244 Inside NCR METRO_MANILA Parañaque City San Antonio 15 1 22 245 Inside NCR METRO_MANILA Parañaque City San Isidro 15 1 22 246 Inside NCR METRO_MANILA Parañaque CityB.F.Homes 15 1 22 247 Inside NCR METRO_MANILA Parañaque CityB.F.Homes 15 1 22 248 Inside NCR METRO_MANILA Parañaque CityB.F.Homes 15 1 22 249 Inside NCR METRO_MANILA Pasay_City NAIA 2 1 5 250 Inside NCR METRO_MANILA Parañaque_City Marina Manila Baytown 15 1 22 251 Inside NCR METRO_MANILA Muntinlupa_City Sucat 16 1 23 252 Inside NCR METRO_MANILA Muntinlupa_City Cupang 16 1 23 253 Inside NCR METRO_MANILA Muntinlupa_City Alabang 16 1 23 254 Inside NCR METRO_MANILA Muntinlupa_City New Alabang Village 16 1 23 255 Inside NCR METRO_MANILA Muntinlupa_City Putatan 16 1 23 256 Inside NCR METRO_MANILA Muntinlupa_City Poblacion(Muntinlupa) 16 1 23 257 Inside NCR METRO_MANILA Muntinlupa_City Tunasan 16 1 23 258 Inside NCR METRO_MANILA Las_Piñas_City Manuyo 17 1 24 259 Inside NCR METRO_MANILA Las_Piñas_City Elias Aldana/Daniel Fajardo 17 1 24 260 Inside NCR METRO_MANILA Las_Piñas_City Pulang Lupa 17 1 24 261 Inside NCR METRO_MANILA Las_Piñas_City Pamplona 17 1 24 262 Inside NCR METRO_MANILA Las_Piñas_City B.F.International 17 1 24 263 Inside NCR METRO_MANILA Las_Piñas_City Talon 17 1 24 264 Inside NCR METRO_MANILA Las_Piñas_City Pilar 17 1 24 265 Inside NCR METRO_MANILA Las_Piñas_City Almanza 17 1 24 266 Inside III BULACAN Obando Obando 18 2 25 267 Inside III BULACAN Marilao Marilao(West) 19 2 26 268 Inside III BULACAN Meycauayan Meycauayan(West) 20 2 27 269 Inside III BULACAN San_Jose_del MSJDM(West) 21 2 28 270 Inside III BULACAN Norzagaray Norzagaray 22 2 29 271 Inside III BULACAN Santa_Maria Santa Maria(SW) 23 2 30 272 Inside III BULACAN Bocaue Bocaue 24 2 31 273 Inside III BULACAN Bulacan Bulacan 25 2 32 274 Inside III BULACAN Balagtas_(Bigaa) Balagtas 26 2 33 275 Inside III BULACAN Pandi Pandi 27 2 34 276 Inside III BULACAN Guiguinto Guiguinto 28 2 35 277 Inside III BULACAN Plaridel Plaridel 29 2 36

A-4

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 278 Inside III BULACAN Pulilan Pulilan 30 2 37 279 Inside III BULACAN Malolos_(Capital) Malolos(North) 31 2 38 280 Inside III BULACAN Paombong Paombong 32 2 39 281 Inside III BULACAN Hagonoy Hagonoy 33 2 40 282 Inside III BULACAN Calumpit Calumpit 34 2 41 283 Inside IV-A CAVITE GMA Gen. Mariano Alvarez 35 4 42 284 Inside IV-A CAVITE Dasmari}as Dasmarinas(West) 36 4 43 285 Inside IV-A CAVITE Bacoor Bacoor(North) 37 4 44 286 Inside IV-A CAVITE Imus Imus(North) 38 4 45 287 Inside IV-A CAVITE Kawit Kawit 39 4 46 288 Inside IV-A CAVITE Cavite_City Cavite City 40 4 47 289 Inside IV-A CAVITE Noveleta Noveleta 41 4 48 290 Inside IV-A CAVITE Rosario Rosario 42 4 49 291 Inside IV-A CAVITE General_Trias General Trias(North) 43 4 50 292 Inside IV-A CAVITE Tanza Tanza(North) 44 4 51 293 Inside IV-A CAVITE Trece_Martires Trece Martires 45 4 52 294 Inside IV-A CAVITE Naic Naic 46 4 53 295 Inside IV-A CAVITE Silang Silang(West) 47 4 54 296 Inside IV-A CAVITE Carmona Carmona 48 4 55 297 Inside IV-A LAGUNA San_Pedro San Pedro(North) 49 5 56 298 Inside IV-A LAGUNA Bi}an Binan(North) 50 5 57 299 Inside IV-A LAGUNA Santa_Rosa Santa Rosa(Center) 51 5 58 300 Inside IV-A LAGUNA Cabuyao Cabuyao(North) 52 5 59 301 Inside IV-A LAGUNA City_of_Calamba City of Calamba(Center) 53 5 60 302 Inside IV-A LAGUNA Los_Ba}os Los Banos 54 5 61 303 Inside IV-A RIZAL Taytay Taytay(West) 55 3 62 304 Inside IV-A RIZAL Cainta Cainta(South) 56 3 63 305 Inside IV-A RIZAL Antipolo Antipolo(Center) 57 3 64 306 Inside IV-A RIZAL San_Mateo San Mateo(South) 58 3 65 307 Inside IV-A RIZAL Rodriguez Rodriguez(West) 59 3 66 308 Inside IV-A RIZAL Angono Angono 60 3 67 309 Inside IV-A RIZAL Binangonan Binangonan(North) 61 3 68 310 Inside IV-A RIZAL Cardona Cardona 62 3 69 311 Inside IV-A RIZAL Morong Morong 63 3 70 312 Inside IV-A RIZAL Teresa Teresa 64 3 71 313 Inside IV-A RIZAL Baras Baras 65 3 72 314 Inside IV-A RIZAL Tanay Tanay 66 3 73 315 Inside IV-A RIZAL Pililia Pililia 67 3 74 316 Inside IV-A RIZAL Jalajala Jalajala 68 3 75 317 Inside NCR METRO_MANILA CALOOCAN_CITY North 2(CN) 8 1 15 318 Inside NCR METRO_MANILA Manila Manila Harbour Center 1 1 1 319 Inside NCR METRO_MANILA Manila Manila South Harbour 1 1 4 320 Inside NCR METRO_MANILA Para}aque_City NAIA Terminal 1 15 1 22 321 Inside NCR METRO_MANILA Pasay_City NAIA Terminal 2 2 1 5 322 Inside NCR METRO_MANILA Pasay_City NAIA Terminal 3 2 1 5 323 Inside NCR METRO_MANILA Pasay_City NAIA Domestic Terminal 2 1 5 324 Inside III BULACAN Marilao Marilao(East) 19 2 26 325 Inside III BULACAN Meycauayan Meycauayan(East) 20 2 27 326 Inside III BULACAN San_Jose DMSJDM(East) 21 2 28 327 Inside III BULACAN San_Jose DM SJDM(North) 21 2 28 328 Inside III BULACAN Santa_Maria Santa Maria(NE) 23 2 30 329 Inside III BULACAN Malolos_(Capital) Malolos(South) 31 2 38 330 Inside IV-A CAVITE Dasmari}as Dasmarinas(Center) 36 4 43 331 Inside IV-A CAVITE Dasmari}as Dasmarinas(East) 36 4 43 332 Inside IV-A CAVITE Dasmari}as Dasmarinas(South) 36 4 43 333 Inside IV-A CAVITE Bacoor Bacoor (Coastal) 37 4 44 334 Inside IV-A CAVITE Bacoor Bacoor(Center) 37 4 44 335 Inside IV-A CAVITE Bacoor Bacoor(South) 37 4 44 336 Inside IV-A CAVITE Imus Imus(Center) 38 4 45 337 Inside IV-A CAVITE Imus Imus(South) 38 4 45 338 Inside IV-A CAVITE General_Trias General Trias(South) 43 4 50 339 Inside IV-A CAVITE Tanza Tanza(South) 44 4 51 340 Inside IV-A CAVITE Silang Silang(Eest) 47 4 54 341 Inside IV-A LAGUNA San_Pedro San Pedro(South) 49 5 56 342 Inside IV-A LAGUNA Bi}an Binan(South) 50 5 57 343 Inside IV-A LAGUNA Santa_Rosa Santa Rosa(West) 51 5 58 344 Inside IV-A LAGUNA Cabuyao Cabuyao(South) 52 5 59 345 Inside IV-A LAGUNA City_of_Calamba City of Calamba(West) 53 5 60 346 Inside IV-A LAGUNA City_of_Calamba City of Calamba(East) 53 5 60 347 Inside IV-A RIZAL Taytay Taytay(East) 55 3 62

A-5

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 348 Inside IV-A RIZAL Cainta Cainta(North) 56 3 63 349 Inside IV-A RIZAL Antipolo Antipolo(South) 57 3 64 350 Inside IV-A RIZAL Antipolo Antipolo(North) 57 3 64 351 Inside IV-A RIZAL Antipolo Antipolo(North-East) 57 3 64 352 Inside IV-A RIZAL San_Mateo San Mateo(North) 58 3 65 353 Inside IV-A RIZAL Rodriguez Rodriguez(East) 59 3 66 354 Inside IV-A RIZAL Binangonan Binangonan(South) 61 3 68 355 Outside III BULACAN Bustos Bustos(BULACAN) 69 6 76 356 Outside III BULACAN Baliuag Baliuag(BULACAN) 69 6 76 357 Outside III BULACAN Angat Angat(BULACAN) 69 6 76 358 Outside III BULACAN San_Rafael San_Rafael(BULACAN) 69 6 76 359 Outside III BULACAN San_Ildefonso San_Ildefonso(BULACAN) 69 6 76 Do}a_Remedios_ 360 Outside III BULACAN Do}a_Remedios_Trinidad 69 6 76 Trinidad 361 Outside III BULACAN San_Miguel San_Miguel(BULACAN) 69 6 76 362 Outside IV-A CAVITE Tagaytay Tagaytay(CAVITE) 70 7 77 363 Outside IV-A CAVITE Amadeo Amadeo(CAVITE) 70 7 77 364 Outside IV-A CAVITE Indang Indang(CAVITE) 70 7 77 365 Outside IV-A CAVITE Mendez Mendez(CAVITE) 70 7 77 366 Outside IV-A CAVITE Alfonso Alfonso(CAVITE) 70 7 77 Gen._Emilio_Agui 367 Outside IV-A CAVITE Gen._Emilio_Aguinaldo(CAVITE) 70 7 77 naldo 368 Outside IV-A CAVITE Magallanes Magallanes(CAVITE) 70 7 77 369 Outside IV-A CAVITE Maragondon Maragondon(CAVITE) 70 7 77 370 Outside IV-A CAVITE Ternate Ternate(CAVITE) 70 7 77 371 Outside IV-A LAGUNA Bay Bay(LAGUNA) 71 7 78 372 Outside IV-A LAGUNA Calauan Calauan(LAGUNA) 71 7 78 373 Outside IV-A LAGUNA Victoria Victoria(LAGUNA) 71 7 78 374 Outside IV-A LAGUNA Pila Pila(LAGUNA) 71 7 78 375 Outside IV-A LAGUNA Santa_Cruz Santa_Cruz(LAGUNA) 71 7 78 376 Outside IV-A LAGUNA Alaminos Alaminos(LAGUNA) 71 7 78 377 Outside IV-A LAGUNA San_Pablo_City San_Pablo_City(LAGUNA) 71 7 78 378 Outside IV-A LAGUNA Nagcarlan Nagcarlan(LAGUNA) 71 7 78 379 Outside IV-A LAGUNA Rizal Rizal(LAGUNA) 71 7 78 380 Outside IV-A LAGUNA Liliw Liliw(LAGUNA) 71 7 78 381 Outside IV-A LAGUNA Majayjay Majayjay(LAGUNA) 71 7 78 382 Outside IV-A LAGUNA Magdalena Magdalena(LAGUNA) 71 7 78 383 Outside IV-A LAGUNA Luisiana Luisiana(LAGUNA) 71 7 78 384 Outside IV-A LAGUNA Cavinti Cavinti(LAGUNA) 71 7 78 385 Outside IV-A LAGUNA Pagsanjan Pagsanjan(LAGUNA) 71 7 78 386 Outside IV-A LAGUNA Lumban Lumban(LAGUNA) 71 7 78 387 Outside IV-A LAGUNA Kalayaan Kalayaan(LAGUNA) 71 7 78 388 Outside IV-A LAGUNA Paete Paete(LAGUNA) 71 7 78 389 Outside IV-A LAGUNA Pakil Pakil(LAGUNA) 71 7 78 390 Outside IV-A LAGUNA Pangil Pangil(LAGUNA) 71 7 78 391 Outside IV-A LAGUNA Siniloan Siniloan(LAGUNA) 71 7 78 392 Outside IV-A LAGUNA Famy Famy(LAGUNA) 71 7 78 393 Outside IV-A LAGUNA Mabitac Mabitac(LAGUNA) 71 7 78 394 Outside IV-A LAGUNA Santa_Maria Santa_Maria(LAGUNA) 71 7 78 395 Outside I ILOCOS_NORTE ADAMS ADAMS(ILOCOS_NORTE) 72 8 79 396 Outside I ILOCOS_SUR ALILEM ALILEM(ILOCOS_SUR) 72 8 79 397 Outside I LA_UNION AGOO AGOO(LA_UNION) 72 8 79 398 Outside I PANGASINAN AGNO AGNO(PANGASINAN) 72 8 79 399 Outside CAR ABRA BANGUED BANGUED_(Capital)(ABRA) 73 8 80 400 Outside CAR BENGUET ATOK ATOK(BENGUET) 73 8 80 401 Outside CAR IFUGAO BANAUE BANAUE(IFUGAO) 73 8 80 402 Outside CAR KALINGA&APAYAO KALINGA_and_APAYAO 73 8 80 MOUNTAIN_PROVI 403 Outside CAR BARLIG BARLIG(MOUNTAIN_PROVINCE) 73 8 80 NCE 404 Outside II BATANES BASCO_(Capital) BASCO_(Capital)(BATANES) 74 8 81 405 Outside II CAGAYAN ABULUG ABULUG(CAGAYAN) 74 8 81 406 Outside II ISABELA ALICIA ALICIA(ISABELA) 74 8 81 407 Outside II NUEVA_VIZCAYA AMBAGUIO AMBAGUIO(NUEVA_VIZCAYA) 74 8 81 408 Outside II QUIRINO AGLIPAY AGLIPAY(QUIRINO) 74 8 81 409 Outside III BATAAN ABUCAY ABUCAY(BATAAN) 75 6 82 410 Outside III NUEVA_ECIJA ALIAGA ALIAGA(NUEVA_ECIJA) 75 6 82 411 Outside III PAMPANGA ANGELES_CITY ANGELES_CITY(PAMPANGA) 75 6 82 412 Outside III TARLAC ANAO ANAO(TARLAC) 75 6 82 413 Outside III ZAMBALES BOTOLAN BOTOLAN(ZAMBALES) 75 6 82 414 Outside III AURORA BALER_(Capital) BALER_(Capital)(AURORA) 75 6 82

A-6

MUCEP Large Medium Area Region Province City/Mun Zone_Name Mun/Prov Zone (Small) Zone Zone 415 Outside IV-A BATANGAS AGONCILLO AGONCILLO(BATANGAS) 76 7 83 416 Outside IV-B MARINDUQUE BOAC_(Capital) BOAC_(Capital)(MARINDUQUE) 76 7 83 OCCIDENTAL_MIN ABRA_DE_ILOG(OCCIDENTAL_ 417 Outside IV-B ABRA_DE_ILOG 76 7 83 DORO MINDORO) ORIENTAL_MINDO 418 Outside IV-B BACO BACO(ORIENTAL_MINDORO) 76 7 83 RO 419 Outside IV-B PALAWAN ABORLAN ABORLAN(PALAWAN) 76 7 83 420 Outside IV-A QUEZON AGDANGAN AGDANGAN(QUEZON) 76 7 83 421 Outside IV-B ROMBLON ALCANTARA ALCANTARA(ROMBLON) 76 7 83 422 Outside V ALBAY BACACAY BACACAY(ALBAY) 77 8 84 CAMARINES_NOR 423 Outside V BASUD BASUD(CAMARINES_NORTE) 77 8 84 TE 424 Outside V CAMARINES_SUR BAAO BAAO(CAMARINES_SUR) 77 8 84 425 Outside V CATANDUANES BAGAMANOC BAGAMANOC(CATANDUANES) 77 8 84 426 Outside V MASBATE AROROY AROROY(MASBATE) 77 8 84 427 Outside V SORSOGON BARCELONA BARCELONA(SORSOGON) 77 8 84 428 Outside VI Region_VI 78 8 85 429 Outside VII Region_VII 79 8 86 430 Outside VIII Region_VIII 80 8 87 IX_X_XI_ 431 Outside XII_XIII_A Region_IX_X_XI_XII_XIII_ARMM 81 888 RMM 432 Outside Out All_Foreign_Countries 82 8 89

A-7

APPENDIX B: POPULATION TRENDS IN MUCEP AREA Table B-1: Population in 2014 Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 1 Divisoria/Zaragosa 155,046 123,251 1,508 1,017 4,217 2,648 52,212 39,689 18,035 15,092 15,471 1,384 2 Tondo/Moriones 125,999 106,363 829 1,425 2,755 1,123 42,246 29,825 15,472 13,231 10,757 7,084 3 Tondo/Herbosa 103,121 89,852 343 1,214 3,514 2,688 35,168 24,674 11,389 12,809 10,468 6,222 4 Tondo/H.Lopez 48,797 45,360 277 344 1,505 2,311 15,321 13,631 6,439 6,210 5,299 2,903 12,70 5 Tondo/J.Luna 86,939 80,978 367 433 2,423 1,595 27,536 21,099 9,401 8,532 10,583 8 6 Tondo/Corregidor 35,169 32,022 0 158 2,289 1,141 10,967 7,864 3,486 5,334 2,951 2,048 La Loma/Chinese 7 20,358 17,331 75 157 767 1,425 7,605 6,518 1,593 768 1,925 48 Cemetery 8 Tondo/J.A.Santos 47,251 35,865 539 831 1,132 621 15,325 9,818 4,825 4,073 5,988 1,118 9 Sta.Cruz/J.A.Santos 62,790 66,234 82 308 1,319 2,073 25,107 28,771 5,393 8,896 7,433 2,589 10 Divisoria/Del Pan 25,592 45,318 197 627 1,168 1,591 9,034 17,730 1,554 6,336 2,048 7,268 11 Binondo/J.Luna 5,315 12,344 0 375 321 626 2,823 8,440 176 280 360 986 Binondo/Reina 12 8,829 23,954 0 407 112 2,525 2,975 16,095 1,430 226 907 1,208 Regente 13 Binondo/Mesericordia 5,673 10,171 43 172 80 398 2,038 6,346 146 0 978 761 14 Quiapo/Carriedo 4,867 27,047 45 751 45 2,055 2,977 17,535 54 170 287 4,442 15 Sta.Cruz/D.Jose 20,575 21,093 0 0 290 766 6,994 6,479 2,611 316 2,737 4,961 16 Sta.Crus/Bambang 37,063 40,042 194 97 580 1,195 14,675 14,172 2,571 6,683 3,890 2,658 17 Sta.Cruz/San Lazaro 35,808 51,169 383 436 857 2,232 14,289 25,409 3,368 5,826 3,702 4,212 18 Quiapo/Globo de Oro 10,771 12,051 75 108 62 239 4,107 3,241 1,077 335 1,500 4,030 19 Quiapo/Bilibid Viejo 11,514 23,977 73 309 313 287 4,797 5,263 1,141 3,795 638 9,684 25,46 20 Sampaloc/FEU/UE 12,673 39,414 51 237 660 820 4,129 4,563 1,451 2,526 1,212 2 Sta.Mesa/Lardizabal 21 13,203 19,239 41 172 264 205 4,362 4,987 1,530 488 1,114 7,400 Ext. Sta.Mesa/Peereza 22 20,205 14,614 178 224 421 386 7,717 3,358 1,370 636 1,778 1,268 Ext. 23 Sampaloc/NU 36,929 26,965 67 239 1,498 1,117 12,192 7,566 3,311 3,539 6,276 896 24 Sampaloc/UST 6,965 19,008 14 14 200 1,042 3,028 5,538 228 320 772 9,371 25 Sampaloc/Florentino 33,874 40,095 411 579 1,704 1,766 10,859 9,113 2,118 5,303 3,359 7,668 26 Sampaloc/Calamba 22,191 20,370 141 473 486 665 6,961 7,187 3,314 120 2,266 2,842 27 Sampaloc/S.Loyola 39,524 36,004 51 0 887 451 13,719 10,713 3,410 7,467 4,441 369 28 Sta.Mesa/Altura Ext. 54,565 43,408 197 333 1,707 1,146 19,946 12,484 3,112 4,232 5,074 1,114 29 Old Sta.Mesa/V.Mapa 50,801 43,484 197 698 2,435 2,254 17,456 13,410 4,743 711 4,313 4,758 30 Sta.Mesa/P.Sanchez 26,034 23,817 195 251 964 928 9,402 6,907 1,510 2,956 2,245 1,623 31 Punta 41,566 31,606 153 252 1,313 833 12,447 8,043 3,846 2,268 4,432 939 Sta.Mesa/R.Magsays 30,96 32 25,683 55,837 0 493 966 1,848 8,602 9,091 2,669 3,079 3,462 ay 1 33 San Miguel/J.P.Laurel 6,670 16,460 914 296 95 90 2,195 3,490 566 724 537 9,458 34 Quiapo/C.Palanca 9,745 7,869 0 0 61 0 2,795 1,799 1,080 937 677 0 35 South Port Area 6,056 4,996 0 0 77 141 1,960 3,079 1,567 0 651 57 16,74 36 Intramuros/Muralla 5,973 34,030 53 916 119 1,212 2,522 12,443 824 247 162 6 28,20 37 Intramuros/Arroceros 3,049 55,463 0 723 75 1,801 1,178 21,929 216 721 267 2 38 Intramuros/Tanque 4,163 9,970 42 679 256 1,082 1,313 2,509 480 347 508 3,788 39 Ermita 4,392 30,298 0 316 0 1,817 1,689 25,156 541 94 482 938 40 Paco/Apacible 11,802 19,087 0 357 275 908 4,758 8,492 1,614 2,835 1,416 2,756 41 Paco/Canociga 24,304 22,301 209 174 1,213 551 6,910 4,200 2,038 2,909 2,227 2,839 42 Paco/Linao (Dart) 8,226 6,021 43 428 0 0 3,616 2,641 896 0 719 0 43 Malate/PCU 7,105 11,553 501 390 94 146 2,361 3,383 364 2,231 886 2,406 44 Malate/J.C.Bocobo 14,133 28,820 49 385 354 915 5,522 14,892 1,006 5,380 2,167 2,072 45 Malate/Harrison Plaza 17,723 20,255 0 342 812 1,515 6,716 9,987 2,183 131 1,379 1,647 46 San Andres/L.Guinto 40,216 29,319 117 536 2,512 866 13,934 9,008 2,578 484 4,564 1,758 47 San Andres/SSH 17,143 12,247 70 17 919 590 7,256 4,782 702 0 1,498 159 48 San Andres/Diamante 27,333 17,876 163 33 2,140 416 9,041 6,285 2,953 269 1,996 25 49 Paco/Fabie 19,936 19,407 50 32 737 419 4,699 4,013 1,555 3,235 1,979 703 50 Sta.Ana/Estrada 72,046 49,872 195 102 2,154 827 23,300 10,865 4,762 625 5,923 1,741 San 51 10,030 11,142 0 93 383 783 2,354 3,426 659 201 1,420 1,425 Miguel/Malacanang 52 Pandacan/Beata 49,873 37,608 718 452 1,926 674 18,436 10,150 2,580 2,766 3,568 842 53 Pandacan/T.Claudio 25,086 16,478 116 116 889 388 7,747 2,731 3,246 1,129 2,758 1,863 54 Sta.Ana/Panaderos 20,016 20,658 183 272 839 817 6,013 4,516 2,101 4,933 1,950 997 55 Manila Noth Harbour 0 0 0 0 0 0 0 0 0 0 0 0

B-1

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 56 MICT 0 0 0 0 0 0 0 0 0 0 0 0 57 BASECO 60,148 45,483 834 498 3,361 1,382 17,419 10,324 7,073 5,791 6,465 2,407 58 San Jose 25,099 25,584 461 970 373 753 4,062 4,467 2,388 3,839 2,557 325 59 San Isidro 20,033 16,196 113 228 467 459 5,940 3,037 2,205 1,698 1,706 848 60 Sta.Clara/Leveriza 20,689 20,235 142 283 277 511 4,037 5,387 2,850 984 2,223 1,812 61 Sta.Clara/Tramo 24,063 26,600 772 346 896 551 5,325 5,112 2,730 4,397 2,767 4,597 62 San Rafael 23,253 40,848 338 1,205 325 1,527 6,850 14,124 3,988 5,634 2,384 8,597 63 San Roque 44,755 37,968 206 59 790 896 11,460 7,959 5,878 5,204 3,237 873 64 Tabon 27,304 23,577 73 182 1,046 429 7,742 8,536 3,490 176 1,454 666 65 Malibay 72,090 66,441 1,035 1,077 2,438 1,438 19,737 14,032 10,546 12,016 5,521 5,125 66 Maricaban 55,725 43,464 373 445 1,623 817 13,595 9,610 7,874 5,196 4,947 255 67 Sto.Nino(Pasay) 27,534 18,604 424 137 568 474 7,218 3,802 2,741 337 2,718 80 68 Villamore Air Base 24,545 31,162 329 424 0 820 3,949 4,753 1,364 4,124 2,550 4,688 69 Air Cargo 22,802 23,921 1,309 570 827 378 5,577 3,649 2,786 6,052 2,130 2,888 70 Domestic Airport 4,262 4,473 322 66 66 124 1,205 1,813 316 79 391 429 PICC(reclamation 71 1,414 13,930 3561,482 0 2,077 40 9,506 310 0 0 69 area) CITE(reclamation 72 2,021 22,107 112 1,185 95 2,915 619 17,347 759 108 0 25 area) 73 Bangkal 25,487 32,019 348 371 687 1,957 5,121 7,832 3,811 4,743 2,172 3,480 74 Palanan 23,406 31,914 1,067 275 548 1,623 4,034 12,486 2,097 2,561 2,782 1,839 75 Pio Del Pilar 36,384 48,983 433 1,028 404 2,542 10,497 18,666 5,451 6,303 3,394 3,598 76 Tejeros 32,062 27,712 368 175 1,130 1,170 7,788 5,534 4,055 4,722 1,719 239 77 Olympia 31,837 36,190 42 434 903 1,881 7,339 10,186 3,700 5,736 3,535 1,592 78 Poblacion(Makati) 22,397 37,820 349 1,015 563 3,677 7,652 15,963 2,957 2,436 1,814 5,280 79 Legaspi Village 4,462 17,948 0 1,140 0 1,858 1,426 11,803 0 0 388 405 80 San Lorenzo 2,901 32,387 0 1,497 0 3,855 670 22,804 0 0 480 1,746 81 Ayala Center 0 25,273 0 919 0 3,153 0 20,803 0 0 0 0 82 Salcedo Village 5,751 23,912 0 2,799 0 1,855 3,936 16,831 0 0 0 503 83 Bel-Air II 1,745 6,888 0 200 0 508 953 4,723 0 109 0 556 84 Urdaneta 2,300 26,247 0 883 0 2,938 347 20,229 59 0 0 92 85 Bel-Air I 5,059 20,189 1871,208 0 1,355 2,750 15,286 0 0 0 0 86 Guadalupe Viejo 19,203 20,759 103 739 516 1,165 4,485 5,710 3,641 3,561 1,382 705 87 Guadalupe Nuevo 37,248 44,610 1,285 747 836 1,240 8,365 14,918 5,297 5,593 2,825 3,640 88 Cembo 43,749 33,437 387 87 669 491 11,860 5,680 4,198 5,201 5,395 738 89 Post Proper Northside 7,331 3,513 662 84 0 0 1,653 434 1,316 350 1,056 0 15,88 90 Rembo 57,987 58,437 762 264 2,660 995 13,067 5,591 7,247 8,015 6,621 1 91 Pembo 150,045 118,062 1,935 1,072 2,529 1,534 34,384 15,819 20,912 18,103 13,579 5,428 92 Fort Bonifacio 23,183 76,743 908 2,824 747 11,305 2,979 43,343 3,343 2,496 1,908 3,217 93 Pinagsama 23,651 27,236 1,005 643 482 841 2,908 4,670 1,555 3,112 920 1,286 94 Dasmarinas/Forbs 5,103 8,988 0 771 0 1,076 1,623 3,755 316 658 532 0 95 Magallanes 4,052 13,419 0 218 0 1,336 1,609 9,591 342 0 725 806 96 Plainview 59,363 62,738 449 1,443 1,208 1,580 11,941 12,895 4,921 5,519 4,992 4,982 97 Old Zaniga 29,048 25,099 339 34 518 728 6,128 2,894 1,095 578 896 793 Poblacion(Mandaluyo 98 37,358 38,025 94 338 1,357 664 10,384 11,109 4,628 4,667 4,193 4,285 ng) 10,06 99 Hagdang Bato 33,040 42,442 502 245 517 1,334 7,564 6,829 2,837 5,438 2,641 4 100 Addition Hills 98,902 87,678 2,461 1,589 3,287 975 14,085 10,249 12,847 11,903 7,525 4,486 101 Barangka 33,916 45,353 507 912 1,424 2,812 8,295 15,290 2,851 1,611 3,614 7,650 102 Highway Hills 57,597 75,603 722 1,383 1,515 3,371 14,383 28,752 6,111 6,373 4,983 6,064 Wack- 103 9,823 52,588 0 3,395 0 8,009 0 39,457 0 0 0 625 Wack/Greenhills 104 Ortigas Center 0 13,757 0 693 0 2,408 0 10,567 0 0 0 0 105 East Greenhills 2,147 6,190 0 0 0 545 0 5,414 0 0 0 232 Greenhills Com'l 106 8,210 15,582 0 90 0 1,067 3,149 8,916 0 292 551 257 Center 107 West Crame 15,668 11,407 328 193 0 73 3,582 1,254 1,473 714 1,127 0 108 Batis 51,609 39,392 885 110 1,262 866 10,697 4,387 4,721 3,433 4,383 756 109 Corazon De Jesus 44,883 48,961 356 656 464 795 9,125 9,169 3,314 5,840 2,899 3,663 110 Dona Imelda 29,859 37,374 788 819 907 1,608 8,541 11,005 3,055 4,231 2,455 5,117 111 Santo Nino 29,368 31,350 196 90 1,029 484 8,110 8,343 2,041 4,127 1,779 2,165 112 Tatalon 65,531 54,770 1,056 988 2,222 1,275 12,731 8,734 7,831 5,600 5,121 1,596 113 Santa Teresita 21,150 26,752 344 305 649 1,286 5,816 10,902 1,840 1,979 437 104 N.S.Amoranto(Ginton 114 25,530 24,290 675 881 815 776 5,576 4,785 2,468 1,130 2,060 2,578 g Silahis) 115 Manresa 36,341 30,425 446 213 552 1,268 8,292 7,726 5,903 1,887 2,661 951 116 Balingasa 28,850 29,469 3,284 3,099 1,752 1,712 6,476 9,364 1,619 2,093 3,465 947

B-2

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 117 Apolonio Samson 39,244 45,568 680 890 1,224 1,729 7,004 13,666 2,754 3,247 2,006 383 118 Masambong 18,958 22,410 510 723 958 640 5,124 4,211 1,561 3,799 892 3,255 Santo 119 14,107 16,364 222 761 570 1,112 4,181 7,361 1,740 58 485 465 Domingo(Matalahib) 120 Del Monte 55,469 60,039 956 1,141 2,212 5,000 14,141 15,311 5,977 7,218 3,636 3,058 121 San Antonio 25,351 19,516 479 437 850 769 7,178 5,236 3,670 1,916 2,408 297 122 Veterans Village 22,909 29,925 1,007 1,005 469 1,719 4,393 8,399 4,149 5,776 1,923 1,933 123 Phil-Am 7,865 10,802 0 379 757 1,223 2,871 5,533 1,096 740 406 66 124 South Triangle 12,735 30,704 87 1,553 87 3,167 2,513 16,969 1,231 415 538 264 125 Kamuning 27,308 38,408 890 1,285 475 2,139 7,985 12,564 2,158 5,959 2,288 3,148 126 Roxas 31,887 34,340 1,053 1,038 640 847 8,863 10,348 3,630 2,942 2,035 3,144 127 Kalusugan 20,435 18,368 499 238 594 467 5,727 6,998 3,209 513 1,581 1,326 128 Mariana 15,931 17,123 110 443 1,088 1,143 1,806 3,734 1,532 414 466 268 129 Kaunlaran 20,985 23,780 1,162 423 547 1,201 4,286 6,369 1,623 2,790 2,502 2,336 Immaculate 130 15,996 16,211 149 277 185 653 4,398 2,220 875 661 1,673 3,750 Concepcion Bagong Lipunan 131 21,613 21,798 528 472 488 1,027 5,012 7,837 2,428 1,008 2,582 911 Crame 132 Crame 4,903 1,682 0 0 0 0 0 1,302 0 243 0 228 133 Ugong Norte 10,908 2,509 0 114 0 294 0 1,475 0 0 0 566 134 Camp Aguinaldo 5,428 11,176 0 0 0 478 1,356 4,853 447 493 340 1,998 135 White Plains 15,188 22,329 0 1,116 630 2,578 4,667 10,153 2,597 2,198 1,425 416 136 Murphy District 21,108 71,305 92 2,521 1,883 9,084 6,169 43,716 3,072 1,001 1,063 4,992 Cubao(Araneta 137 0 6,589 0 499 0 2,684 0 3,406 0 0 0 0 Center) 138 E. Rodriguez 24,749 38,021 652 769 377 1,848 6,414 12,273 2,208 4,124 1,795 5,740 13,70 139 San Roque 59,763 72,022 1,193 851 1,044 2,421 14,016 11,120 5,877 10,554 4,712 2 140 Escopa 22,963 31,817 61 2,022 658 2,713 5,781 14,391 1,727 281 2,808 468 141 Quirino 3 14,523 16,894 91 208 396 395 4,197 3,820 1,454 2,159 860 2,968 142 Quirino 2 25,228 29,529 478 1,076 426 1,186 6,530 6,724 1,736 4,187 2,483 2,573 143 Loyola Heights 59,272 51,809 434 594 1,604 1,367 15,651 11,339 6,453 5,570 5,315 3,453 144 Teachers Village 19,839 18,062 770 581 0 1,015 6,480 6,640 1,558 432 1,886 367 145 QMC 65,662 95,474 1,687 4,443 1,308 3,590 18,822 45,594 3,891 4,371 6,247 4,209 146 U.P. Campus 60,769 60,385 1,591 1,651 1,228 1,266 19,094 19,688 4,543 2,278 4,967 5,833 147 Batasan Hills 157,133 139,789 5,166 2,884 6,304 4,020 39,418 25,847 17,878 19,893 14,471 13,115 148 Matandang Balara 74,306 60,004 3,015 1,110 3,488 2,377 18,335 12,969 7,482 4,695 5,387 2,985 149 Holy Spirit 101,028 86,623 3,072 2,301 6,009 2,054 23,037 13,861 9,774 12,939 7,656 5,127 150 Payatas 124,374 92,257 3,537 1,542 5,074 1,983 31,264 13,194 16,061 15,079 11,935 4,078 151 Bagong Silangan 0 0 0 0 0 0 0 0 0 0 0 0 152 Constitution Hills 84,452 64,506 886 81 4,618 1,739 21,805 9,029 8,759 8,064 8,235 5,718 21,26 153 Commonwealth 209,787 211,933 5,682 4,902 6,204 6,593 52,740 48,078 25,115 27,825 17,605 5 154 Fairview 49,789 55,189 1,503 1,137 2,161 2,210 12,922 15,565 5,703 5,706 4,340 8,268 28,41 155 Pasong Putik 98,425 146,310 2,577 4,635 4,871 5,789 19,896 43,048 10,532 12,890 10,770 5 12,29 156 Kaligayahan 99,481 89,889 2,818 1,473 4,764 2,908 20,322 15,651 13,584 11,904 12,060 6 12,02 157 San Agustin 98,267 122,699 1,939 2,325 4,303 9,173 21,928 36,875 13,167 12,562 7,713 8 16,77 158 Gulod 124,801 122,912 3,930 2,516 4,699 3,152 25,969 21,063 13,840 15,674 12,189 9 159 Sauyo 83,170 63,670 1,204 273 2,396 2,133 20,152 7,137 7,984 6,763 8,069 3,878 160 Bagbag 43,173 35,761 472 195 2,854 2,014 8,917 6,235 5,309 5,024 4,234 1,125 161 Tandang Sora 132,870 130,425 3,760 2,449 4,688 3,830 28,025 29,044 13,365 14,536 11,637 9,376 162 Pasong Tamo 91,555 67,331 1,986 816 3,335 1,047 24,058 13,286 10,596 8,505 6,960 494 163 Culiat 71,222 60,764 1,333 536 3,200 758 15,899 10,969 9,286 8,142 6,177 4,955 164 Project 6 69,487 110,054 947 3,711 1,159 4,826 16,593 49,052 6,823 6,299 5,109 6,537 165 Ramon Magsaysay 33,960 44,026 562 1,086 682 1,600 6,983 10,989 2,366 3,195 3,978 7,299 166 Bahay Toro 78,158 72,920 1,669 1,193 3,868 4,284 23,033 21,344 8,237 7,047 4,635 2,900 167 Baesa 72,254 58,796 498 960 3,618 3,235 16,745 9,882 8,810 7,845 6,403 1,774 168 Sangandaan 25,102 27,632 941 669 1,095 814 4,373 4,488 2,618 3,915 2,921 4,001 169 Bo. San Jose 26,661 19,472 1,079 460 544 238 8,443 5,738 3,629 2,459 2,615 157 170 West 3/4 Ave. 33,630 27,436 717 412 771 1,132 6,616 4,896 3,868 2,435 3,682 913 171 A.Mabini 138,655 107,571 1,567 546 3,339 1,453 32,021 15,923 18,343 14,063 10,605 3,205 172 Dagat Dagatan 117,464 99,995 2,741 1,531 3,940 2,999 25,009 17,456 15,617 14,900 10,981 4,034 12,72 173 West 8/10 Ave. 64,932 79,731 1,291 2,221 1,437 2,427 15,150 22,222 7,887 8,609 7,952 0 174 Grace Park 50,427 60,198 628 1,187 1,008 2,513 12,511 16,701 7,017 7,230 4,775 8,032

B-3

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 10,32 175 Sangandaan 19,008 34,361 0 591 127 1,477 3,576 7,918 1,171 995 946 5 176 Bagon Barrio EDSA 18,429 29,118 281 1,261 281 1,567 6,857 9,815 1,444 3,585 744 4,069 177 Bagon Barrio Center 78,036 59,701 1,424 198 4,294 1,592 16,026 8,312 9,901 7,078 7,228 3,352 178 Bagon Barrio East 80,572 68,936 1,621 808 2,840 1,927 15,724 9,845 11,037 11,078 7,525 4,599 179 Bagumbong 1(CN) 126,620 110,396 1,142 863 6,811 3,518 24,316 15,532 18,161 15,530 12,597 11,447 180 Bagumbong 2(CN) 87,208 84,470 1,363 722 3,405 3,721 17,355 15,376 10,380 12,305 7,461 4,926 181 Bagumbong 3(CN) 47,301 42,963 1,390 654 2,234 1,525 8,420 4,713 8,016 9,395 5,063 4,497 15,27 182 Camarin 1(CN) 92,666 88,135 1,061 831 4,842 3,190 25,955 17,963 11,135 12,397 11,259 9 183 Camarin 2(CN) 191,358 167,630 1,441 1,019 6,683 1,449 35,114 21,724 22,755 23,206 13,715 8,782 17,67 184 North 1(CN) 264,546 227,822 2,247 1,440 11,562 4,091 49,310 26,816 35,517 35,825 23,847 7 14,53 185 West(CN) 174,034 143,170 4,066 2,622 9,049 2,659 37,743 19,490 21,442 19,598 17,390 8 186 Canumay 95,958 89,258 1,110 997 5,957 6,772 21,579 16,943 14,320 12,560 8,107 7,083 Mapulang 187 79,589 72,779 3,793 3,516 4,109 3,999 12,424 7,875 10,003 8,968 8,310 7,383 Lupa/Ugong 188 Bagbaguin 27,712 33,881 687 771 1,378 2,731 6,075 10,951 2,849 3,999 2,108 814 189 Hen. T. De Leon 87,080 74,063 3,060 1,470 3,078 951 15,678 7,628 11,746 11,143 6,499 5,658 190 Marulas 51,711 60,801 96 193 502 1,458 5,995 6,141 3,478 4,805 2,616 9,070 191 Karuhatan 88,131 111,399 1,153 1,639 1,617 5,206 13,188 26,722 5,515 7,421 6,175 9,622 192 Maysan 66,515 52,798 1,315 975 4,804 3,132 14,065 8,822 6,058 5,836 8,450 2,306 Malanday(Valenzuela 193 48,409 45,400 828 1,179 882 942 7,942 6,873 4,732 4,371 2,860 1,054 ) 194 Dalandanan 54,622 61,602 216 587 3,481 4,162 10,721 11,620 9,047 9,579 4,757 9,267 195 Maysilo/Panghulo 44,481 36,587 589 243 2,479 994 9,312 5,304 4,964 4,972 3,768 1,847 196 Potrero 39,971 38,950 815 533 1,884 3,020 3,916 3,606 5,794 5,977 3,316 1,568 197 Tugatog 47,553 49,336 405 282 1,403 2,493 14,467 10,824 5,274 8,071 3,483 5,147 198 Longos 61,077 65,244 1,058 1,686 1,416 944 10,530 9,489 6,134 7,367 3,520 7,001 199 Tonsuya 83,311 70,552 1,698 603 2,178 1,079 15,231 11,657 8,585 6,476 5,502 807 200 Baritan/Concepcion 64,051 66,934 1,440 1,746 1,221 874 12,543 12,302 7,296 9,798 7,683 8,022 201 Dampalit 16,823 12,599 538 318 1,523 1,207 3,683 2,031 2,362 1,227 589 0 202 Tanza 26,704 19,714 1,047 341 1,028 157 6,405 3,257 4,329 3,159 2,401 1,304 203 Tangos 52,188 46,394 3,508 2,057 1,109 712 7,312 5,193 6,060 5,766 2,618 1,086 204 San Jose 61,825 66,147 536 884 885 1,245 7,479 8,447 3,757 5,747 2,438 3,355 205 Navotas East/West 44,176 40,610 842 601 1,079 1,336 3,924 3,306 4,455 2,833 1,422 81 206 North Bay Blvd. 75,594 72,548 2,044 3,560 2,578 2,565 11,492 9,607 7,893 7,394 7,188 5,200 207 Navotas Fishport 0 0 0 0 0 0 0 0 0 0 0 0 208 Nangka 41,182 34,011 513 632 2,399 1,157 12,103 7,321 5,991 6,007 3,275 2,365 209 Parang 74,272 77,915 411 306 2,841 3,921 6,731 7,343 2,689 4,653 3,609 3,598 10,99 210 Concepcion(Marikina) 84,564 82,953 1,238 719 4,108 2,185 18,198 16,193 8,358 8,575 8,356 1 211 Marikina Heights 60,458 55,471 631 502 1,816 1,230 12,600 10,733 4,883 3,863 5,166 3,601 Calumpang/San 212 40,400 69,315 683 715 1,178 3,990 9,545 25,430 3,341 6,777 5,159 11,605 Roque 213 Santo Nino 28,125 32,659 686 600 1,190 2,686 8,434 11,387 3,131 3,393 2,165 1,881 214 Malanday(Marikina) 54,079 47,325 666 668 2,282 599 9,814 6,157 3,289 3,148 2,824 1,550 215 Barangka(Marikina) 54,919 52,973 369 171 1,242 1,441 11,481 10,935 4,300 4,775 4,214 2,338 216 Kalawaan 53,332 51,882 816 455 1,612 1,902 7,186 5,857 4,987 6,315 3,962 2,788 12,99 217 Santolan/Manggahan 173,440 187,400 3,794 3,470 6,230 13,448 34,975 45,071 19,933 18,116 14,563 7 218 Santa Lucia 44,231 45,036 562 179 900 1,159 7,448 5,796 4,360 6,047 3,339 4,223 219 Maybunga 34,457 40,296 313 745 1,757 2,873 5,373 5,604 1,774 3,892 2,567 4,509 220 Ugong 21,572 34,347 1,204 1,311 505 3,188 3,379 14,991 2,456 2,741 2,474 460 221 San Antonio 21,141 55,135 83 1,867 83 4,574 2,549 29,485 931 1,193 788 828 222 Kapitolyo 34,474 34,837 659 979 1,420 1,593 9,450 10,145 3,230 2,817 3,686 3,351 223 Bagong Ilog 17,252 16,307 63 377 692 1,088 3,182 3,516 2,089 1,466 1,432 66 224 Bambang 73,614 92,639 1,376 1,473 2,213 3,953 10,769 21,104 5,164 9,061 4,056 6,839 10,84 225 Caniogan 66,495 71,264 1,190 1,550 1,625 1,780 13,535 9,907 5,999 7,809 4,977 8 226 Pinagbuhatan 149,354 128,208 2,040 1,669 4,750 2,414 24,828 14,453 14,635 11,857 11,260 6,271 227 Santa Ana(Pateros) 68,080 65,392 3,068 2,175 2,190 916 17,747 15,155 6,845 7,446 7,006 8,159 228 Bagumbayan 91,014 84,584 1,050 927 4,481 4,004 16,899 11,867 12,621 14,319 6,478 3,983 22,93 229 Bicutan 170,887 162,669 2,804 2,377 6,923 5,912 36,828 28,880 23,382 20,175 18,898 6 230 Signal Village 75,609 74,933 349 220 794 334 9,849 7,655 4,217 6,283 4,239 4,526 231 Western Bicutan 73,046 72,093 1,034 766 3,976 2,690 9,349 10,741 10,117 10,380 7,061 6,012 232 Hagonoy 94,348 79,396 935 806 1,677 886 12,571 5,313 7,270 5,566 6,126 1,001

B-4

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 12,66 233 Ususan 139,833 127,107 3,605 2,756 8,350 5,489 30,536 23,710 19,231 18,980 14,485 1 234 Baclaran 18,789 39,686 369 423 575 1,872 5,887 20,201 2,217 5,124 2,519 4,649 235 Tambo 27,623 32,867 190 765 986 2,383 4,517 9,540 4,265 3,686 1,686 504 236 La Huerta 10,405 16,652 196 81 0 96 2,543 4,608 1,881 3,454 909 3,538 12,99 237 San Dionisio 63,287 73,586 1,145 2,053 892 1,847 18,585 18,752 7,756 10,450 7,992 3 238 Moonwalk 70,395 61,424 1,464 950 4,008 2,706 16,674 10,118 9,349 8,961 6,381 6,303 Santo 239 34,411 36,328 709 845 1,430 1,114 8,913 12,191 4,630 3,914 1,998 1,342 Nino(Paranaque) 240 Merville 23,945 16,755 1,340 723 1,555 1,242 3,950 3,428 3,454 135 2,209 0 241 Sun Valley 60,117 58,254 1,119 857 2,149 2,329 16,425 14,873 7,678 6,613 5,215 6,053 242 Don Bosco 53,538 61,477 512 1,273 2,689 3,427 12,706 18,881 10,106 12,749 4,540 1,943 Marcelo Green 243 30,118 21,734 0 105 1,832 1,224 6,652 4,808 3,988 87 1,475 0 Village 244 San Antonio 64,969 70,131 1,753 461 1,798 2,214 7,686 12,099 6,743 9,953 4,335 2,757 245 San Isidro 78,558 61,071 1,455 301 1,974 1,435 17,202 12,856 14,672 7,342 7,222 3,081 246 B.F.Homes 27,441 23,723 136 253 1,383 940 5,068 3,550 2,327 1,164 1,161 570 247 B.F.Homes 50,722 49,023 1,455 1,221 427 2,029 13,681 12,998 5,690 5,233 2,919 900 248 B.F.Homes 10,198 9,804 232 157 116 124 2,026 2,436 1,276 1,020 603 122 249 NAIA 2,621 4,159 0 0 0 0 655 672 482 1,857 147 292 Marina Manila 250 12,697 11,983 199 288 515 656 2,093 757 2,345 2,246 978 1,677 Baytown 251 Sucat 54,019 58,513 428 908 2,289 3,176 8,732 10,089 4,290 4,281 5,625 7,050 252 Cupang 57,341 46,951 699 721 1,694 2,883 10,417 4,339 7,111 4,394 3,871 876 253 Alabang 97,581 153,694 1,571 3,391 3,727 9,636 18,075 56,227 10,451 16,084 6,320 9,975 254 New Alabang Village 22,219 14,555 2,529 551 382 269 6,386 2,929 1,627 478 1,019 103 255 Putatan 84,448 75,620 1,878 999 3,522 2,669 17,339 13,730 11,189 11,815 7,310 3,686 Poblacion(Muntinlupa 17,69 256 113,263 108,054 1,541 1,661 3,200 1,314 25,956 16,344 12,426 12,371 11,289 ) 9 257 Tunasan 52,044 55,227 1,433 1,480 2,856 3,409 10,105 14,779 7,685 6,793 3,657 2,459 258 Manuyo 55,980 49,481 206 317 2,490 1,535 14,048 9,802 7,618 6,166 4,711 5,089 Elias Aldana/Daniel 259 28,133 24,204 285 478 1,328 474 7,084 3,711 3,577 4,011 1,988 1,974 Fajardo 260 Pulang Lupa 61,900 55,083 631 1,232 2,814 3,698 16,758 13,554 8,414 6,510 4,976 1,796 12,56 261 Pamplona 96,228 104,560 2,642 2,051 4,495 5,651 20,219 17,753 10,631 14,700 6,507 7 262 B.F.International 99,667 91,363 1,873 888 4,285 3,704 23,828 14,623 13,933 15,715 7,053 7,659 263 Talon 100,772 96,967 1,615 1,717 5,368 3,947 19,811 16,734 15,560 16,282 7,427 7,094 264 Pilar 72,115 62,284 1,036 616 3,809 2,152 15,920 11,407 12,023 10,717 4,669 3,119 265 Almanza 72,698 78,875 1,397 1,777 2,471 2,242 8,309 13,364 7,975 9,484 5,365 5,016 266 Obando 61,364 56,138 1,935 1,708 2,547 1,629 13,903 12,410 9,769 9,428 4,527 2,280 267 Marilao(West) 63,598 70,319 534 1,200 3,718 4,623 15,397 18,272 13,784 13,678 5,821 7,998 10,05 268 Meycauayan(West) 127,191 124,676 1,424 1,177 6,861 6,339 31,438 28,765 22,590 23,341 9,925 6 19,88 269 SJDM(West) 197,238 185,160 5,804 6,856 8,541 10,726 54,148 35,735 18,520 18,629 16,902 8 270 Norzagaray 104,724 98,410 4,815 5,159 6,128 5,070 15,778 12,344 19,199 20,095 10,158 7,100 271 Santa Maria(West) 78,584 94,110 1,135 1,572 5,878 7,456 21,843 29,274 12,721 14,706 6,004 9,881 272 Bocaue 110,438 110,971 3,042 3,557 6,975 7,349 23,284 23,446 23,560 23,852 10,606 9,958 273 Bulacan 73,738 68,566 4,134 4,340 4,773 3,589 19,149 17,439 9,879 9,651 5,807 3,551 274 Balagtas 69,879 75,630 1,997 1,661 3,771 4,404 15,740 20,765 11,937 11,212 5,302 6,563 275 Pandi 74,008 70,047 3,408 3,146 2,886 1,671 15,969 13,272 10,069 10,297 4,756 4,800 276 Guiguinto 94,559 95,015 1,460 1,553 5,915 6,457 27,482 28,277 12,114 12,334 9,427 7,557 277 Plaridel 106,132 100,719 1,354 1,462 3,181 2,442 30,264 28,696 22,709 22,598 9,195 6,250 278 Pulilan 89,384 83,398 2,418 2,408 7,750 6,417 24,198 21,217 5,462 5,744 8,147 5,959 32,34 279 Malolos(North) 118,923 139,805 3,943 4,397 3,161 4,181 27,807 29,091 19,021 17,592 12,634 8 280 Paombong 50,716 45,221 3,895 3,906 2,062 792 10,991 8,435 8,198 8,391 4,768 2,894 281 Hagonoy 129,403 116,661 5,615 4,709 3,116 1,595 28,903 22,297 22,333 22,346 10,642 7,588 282 Calumpit 106,916 100,392 1,595 1,378 4,295 4,257 27,557 25,821 12,979 12,443 7,069 3,073 283 Gen. Mariano Alvarez 144,436 128,165 2,295 1,804 9,764 5,259 44,493 34,671 16,895 16,219 9,201 8,646 12,61 284 Dasmarinas(West) 99,934 124,449 2,768 3,649 9,412 7,693 33,772 45,027 10,678 17,314 5,133 0 285 Bacoor(North) 79,558 72,979 1,784 984 3,047 3,989 21,104 18,535 10,255 10,011 4,656 1,140 286 Imus(North) 111,200 126,873 1,299 1,129 10,428 12,638 33,730 41,042 6,481 9,715 4,050 7,248 287 Kawit 82,116 75,679 1,910 1,496 6,964 4,659 21,972 20,101 12,230 11,238 6,482 5,729 288 Cavite City 101,678 93,197 2,310 1,477 5,523 2,732 35,712 31,274 5,307 5,686 7,465 6,908 289 Noveleta 44,956 39,653 503 357 1,973 514 12,844 10,993 5,709 4,470 3,871 3,329 290 Rosario 93,644 150,355 4,548 6,767 10,673 36,441 30,131 52,883 5,958 6,936 3,616 7,281

B-5

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 291 General Trias(North) 102,127 91,979 3,675 2,986 13,404 9,941 33,405 27,489 7,178 6,705 3,011 3,462 292 Tanza(North) 106,985 98,135 4,726 4,303 8,730 2,871 36,048 32,071 4,383 6,147 3,790 3,480 293 Trece Martires 120,676 111,557 1,423 2,151 12,727 10,718 34,993 27,650 15,304 15,403 8,110 8,070 294 Naic 91,782 85,915 6,009 5,319 4,214 1,903 21,663 19,419 15,806 15,806 5,638 4,963 295 Silang(West) 97,462 95,997 2,910 2,350 9,006 7,284 25,054 23,090 18,354 19,290 5,629 7,388 296 Carmona 83,186 90,416 2,239 2,960 8,173 9,693 22,114 27,503 10,880 10,743 5,619 5,479 15,22 297 San Pedro(North) 164,960 148,110 1,354 909 8,166 5,761 42,102 28,711 22,826 21,938 14,845 3 20,65 298 Binan(North) 192,662 201,088 7,304 6,898 8,183 5,946 41,328 45,169 28,306 32,732 18,184 0 20,00 299 Santa Rosa(Center) 248,540 250,704 6,639 6,722 16,930 13,892 55,993 60,182 33,181 32,115 18,639 2 300 Cabuyao(North) 122,908 115,885 3,284 2,836 7,537 7,111 27,717 22,372 17,810 17,894 9,579 8,373 City of 13,75 301 197,356 191,474 8,141 7,359 8,048 5,297 35,344 32,640 30,863 30,748 12,972 Calamba(Center) 8 302 Los Banos 107,759 106,402 3,494 3,220 3,102 2,144 24,053 22,470 15,216 15,198 8,529 10,115 23,20 303 Taytay(West) 222,583 195,338 1,941 1,081 11,951 10,068 51,429 35,318 23,299 22,271 29,667 8 304 Cainta(South) 206,125 166,739 2,426 674 10,335 5,887 43,443 26,210 26,757 20,349 19,400 11,005 27,58 305 Antipolo(Center) 284,928 275,260 8,636 7,892 18,691 16,751 59,513 46,725 36,842 40,862 26,353 9 306 San Mateo(South) 146,003 130,297 1,801 1,042 7,568 5,475 30,059 22,358 15,501 14,720 9,954 5,976 15,41 307 Rodriguez(West) 173,838 160,489 1,106 1,209 9,865 5,996 38,229 27,412 21,023 23,362 16,682 0 14,69 308 Angono 109,996 99,732 1,984 1,733 6,983 4,587 26,276 19,989 11,698 11,539 16,071 7 18,33 18,04 14,96 309 Binangonan(North) 239,300 216,106 12,654 9,470 53,527 39,305 31,175 30,938 19,249 3 2 8 310 Cardona 50,984 44,117 3,030 2,226 2,804 1,834 10,097 7,196 5,213 4,942 5,196 3,422 311 Morong 55,224 57,783 2,649 1,375 2,774 2,330 12,701 10,832 10,702 10,868 5,160 11,184 312 Teresa 50,945 45,765 1,352 1,646 2,681 2,725 14,444 12,301 5,698 5,803 5,246 1,669 313 Baras 34,543 30,769 623 710 2,478 1,574 10,090 8,473 3,052 3,052 4,110 2,771 10,92 314 Tanay 105,696 104,352 5,174 4,834 6,989 6,507 19,787 19,366 16,214 16,346 11,258 9 315 Pililia 62,256 58,857 4,589 4,483 2,739 2,263 9,744 7,149 9,024 9,024 6,662 6,679 316 Jalajala 32,140 29,659 2,367 2,361 1,224 743 6,909 5,995 5,090 5,090 3,126 2,162 317 North 2(CN) 19,846 15,470 0 501 1,233 423 4,594 2,312 2,162 2,436 2,332 391 Manila Harbour 318 0 0 0 0 0 0 0 0 0 0 0 0 Center 319 Manila South Harbour 0 0 0 0 0 0 0 0 0 0 0 0 320 NAIA Terminal 1 0 4,570 0 376 0 503 0 3,691 0 0 0 0 321 NAIA Terminal 2 0 1,691 0 368 0 0 0 1,323 0 0 0 0 322 NAIA Terminal 3 0 2,492 0 0 0 280 0 2,212 0 0 0 0 NAIA Domestic 323 0 1,005 0 0 0 0 0 1,005 0 0 0 0 Terminal 10,86 324 Marilao(East) 150,684 134,592 1,607 1,071 14,751 10,883 26,055 20,211 29,241 28,151 15,032 4 325 Meycauayan(East) 80,691 78,225 1,066 1,283 7,247 9,862 17,311 16,785 17,654 16,721 7,033 3,568 326 SJDM(East) 95,757 87,844 1,363 1,658 6,004 4,329 21,587 18,013 13,753 13,668 9,447 7,239 12,20 327 SJDM(North) 189,302 157,191 7,573 4,596 13,564 5,194 39,225 25,696 30,363 28,902 17,302 5 328 Santa Maria(West) 157,933 143,439 2,811 2,269 6,637 5,426 41,220 34,661 28,043 26,189 13,710 9,477 12,48 329 Malolos(South) 133,648 136,728 5,708 6,176 5,971 4,985 37,234 39,515 20,423 22,379 12,918 0 330 Dasmarinas(Center) 251,132 209,751 2,250 201 20,296 12,524 81,104 58,093 23,880 18,012 11,756 9,304 331 Dasmarinas(East) 138,247 107,963 1,941 1,195 16,697 7,369 32,333 15,864 13,110 11,909 9,500 7,316 332 Dasmarinas(South) 120,387 160,265 2,563 4,120 14,203 30,733 39,682 58,909 12,434 14,026 6,747 7,247 333 Bacoor (Coastal) 193,332 176,559 4,227 4,282 15,834 9,204 46,265 40,730 31,151 29,149 13,256 9,908 10,74 334 Bacoor(Center) 164,881 149,843 2,878 1,300 13,057 11,335 40,304 29,521 23,729 23,774 11,813 0 335 Bacoor(South) 170,333 155,851 2,115 744 13,913 12,546 40,316 32,178 25,405 24,767 10,894 8,513 336 Imus(Center) 141,300 148,435 2,289 2,099 10,827 15,246 36,852 45,258 12,701 11,132 11,595 7,283 337 Imus(South) 102,883 89,474 3,677 2,918 7,280 6,552 27,513 15,650 10,621 9,842 6,022 6,742 10,52 338 General Trias(South) 170,333 167,618 4,394 6,219 22,706 18,198 44,232 44,541 15,113 15,230 11,011 0 339 Tanza(South) 102,147 84,922 5,221 3,993 10,169 4,462 21,207 13,828 12,078 10,369 4,926 4,014 340 Silang(Eest) 134,095 117,388 5,518 5,317 9,562 8,178 41,582 30,759 14,599 14,257 10,694 7,141 341 San Pedro(South) 148,919 147,821 3,131 3,205 8,073 8,898 39,515 37,032 21,602 22,437 10,300 9,759 342 Binan(South) 117,075 120,487 1,547 1,807 7,365 15,404 33,320 34,208 15,705 12,528 11,957 9,274 343 Santa Rosa(West) 59,912 63,753 1,542 1,894 3,459 7,955 13,691 15,948 10,012 9,930 5,023 2,397

B-6

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 14,70 344 Cabuyao(South) 173,306 172,801 4,418 5,665 11,556 11,219 33,284 32,173 25,305 24,639 14,548 3 City of 345 172,857 170,619 3,180 3,021 12,186 12,506 29,761 28,662 24,093 23,876 10,163 9,735 Calamba(West) 346 City of Calamba(East) 55,995 64,197 666 1,129 2,212 4,723 9,150 13,222 7,008 7,504 2,518 2,683 347 Taytay(East) 98,323 102,608 1,300 1,012 8,772 7,237 22,180 26,812 12,591 14,410 8,933 7,399 28,84 348 Cainta(North) 134,240 152,193 1,617 2,840 5,868 7,588 30,518 34,518 17,146 14,801 15,697 1 14,98 349 Antipolo(South) 183,748 177,475 2,151 3,226 10,069 8,655 36,557 32,457 23,462 25,967 19,119 4 350 Antipolo(North) 185,813 147,971 1,338 933 11,538 6,092 38,222 23,122 23,587 16,416 18,448 9,876 351 Antipolo(North-East) 81,629 71,726 891 862 4,700 3,164 11,477 7,371 10,303 9,318 7,272 4,635 352 San Mateo(North) 83,437 72,953 2,033 920 4,157 1,983 16,631 11,695 9,488 9,235 5,793 3,660 10,96 353 Rodriguez(East) 171,024 149,813 1,959 1,610 10,406 7,328 29,843 18,909 26,470 24,071 14,660 4 354 Binangonan(South) 27,604 24,476 5,028 4,039 1,240 737 4,008 3,002 2,246 1,910 2,394 1,771 22,477, 22,449,6 477,6 477,6 1,099, 1,099, 5,293, 5,293, 2,730, 2,730, 1,886, 1,886, Total 415 44 52 50 477 474 660 650 712 719 357 367

Table B-2: Population in 2025

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 1 Divisoria/Zaragosa 155,560 145,065 1,513 1,197 4,231 3,117 52,385 46,714 18,095 17,763 15,522 1,629 2 Tondo/Moriones 126,417 125,188 832 1,677 2,764 1,322 42,386 35,104 15,523 15,573 10,793 8,338 3 Tondo/Herbosa 103,463 105,755 344 1,429 3,526 3,164 35,285 29,041 11,427 15,076 10,503 7,323 4 Tondo/H.Lopez 48,959 53,388 278 405 1,510 2,720 15,372 16,044 6,460 7,309 5,317 3,417 14,95 5 Tondo/J.Luna 87,227 95,310 368 510 2,431 1,877 27,627 24,833 9,432 10,042 10,618 7 6 Tondo/Corregidor 35,286 37,690 0 186 2,297 1,343 11,003 9,256 3,498 6,278 2,961 2,410 La Loma/Chinese 7 20,426 20,398 75 185 770 1,677 7,630 7,672 1,598 904 1,931 56 Cemetery 8 Tondo/J.A.Santos 47,408 42,213 541 978 1,136 731 15,376 11,556 4,841 4,794 6,008 1,316 Sta.Cruz/J.A.Santo 9 62,998 77,957 82 363 1,323 2,440 25,190 33,863 5,411 10,471 7,458 3,047 s 10 Divisoria/Del Pan 25,677 53,339 198 738 1,172 1,873 9,064 20,868 1,559 7,457 2,055 8,554 11 Binondo/J.Luna 5,333 14,529 0 441 322 737 2,832 9,934 177 330 361 1,161 Binondo/Reina 12 8,858 28,194 0 479 112 2,972 2,985 18,944 1,435 266 910 1,422 Regente Binondo/Mesericor 13 5,692 11,971 43 202 80 468 2,045 7,469 146 0 981 896 dia 14 Quiapo/Carriedo 4,883 31,834 45 884 45 2,419 2,987 20,639 54 200 288 5,228 15 Sta.Cruz/D.Jose 20,643 24,826 0 0 291 902 7,017 7,626 2,620 372 2,746 5,839 16 Sta.Crus/Bambang 37,186 47,129 195 114 582 1,407 14,724 16,680 2,580 7,866 3,903 3,128 Sta.Cruz/San 17 35,927 60,225 384 513 860 2,627 14,336 29,906 3,379 6,857 3,714 4,957 Lazaro Quiapo/Globo de 18 10,807 14,184 75 127 62 281 4,121 3,815 1,081 394 1,505 4,743 Oro Quiapo/Bilibid 11,39 19 11,552 28,221 73 364 314 338 4,813 6,194 1,145 4,467 640 Viejo 8 29,96 20 Sampaloc/FEU/UE 12,715 46,390 51 279 662 965 4,143 5,371 1,456 2,973 1,216 9 Sta.Mesa/Lardizab 21 13,247 22,644 41 202 265 241 4,376 5,870 1,535 574 1,118 8,710 al Ext. Sta.Mesa/Peereza 22 20,272 17,201 179 264 422 454 7,743 3,952 1,375 749 1,784 1,492 Ext. 23 Sampaloc/NU 37,051 31,738 67 281 1,503 1,315 12,232 8,905 3,322 4,165 6,297 1,055 11,03 24 Sampaloc/UST 6,988 22,372 14 16 201 1,226 3,038 6,518 229 377 775 0 Sampaloc/Florenti 25 33,986 47,191 412 681 1,710 2,079 10,895 10,726 2,125 6,242 3,370 9,025 no Sampaloc/Calamb 26 22,265 23,975 141 557 488 783 6,984 8,459 3,325 141 2,274 3,345 a Sampaloc/S.Loyol 27 39,655 42,376 51 0 890 531 13,765 12,609 3,421 8,789 4,456 434 a Sta.Mesa/Altura 28 54,746 51,091 198 392 1,713 1,349 20,012 14,694 3,122 4,981 5,091 1,311 Ext.

B-7

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day Old 29 50,970 51,180 198 822 2,443 2,653 17,514 15,783 4,759 837 4,327 5,600 Sta.Mesa/V.Mapa Sta.Mesa/P.Sanch 30 26,120 28,032 196 295 967 1,092 9,433 8,129 1,515 3,479 2,252 1,910 ez 31 Punta 41,704 37,200 154 297 1,317 980 12,488 9,467 3,859 2,669 4,447 1,105 Sta.Mesa/R.Magsa 36,44 32 25,768 65,720 0 580 969 2,175 8,631 10,700 2,678 3,624 3,473 ysay 1 San 11,13 33 6,692 19,373 917 348 95 106 2,202 4,108 568 852 539 Miguel/J.P.Laurel 2 34 Quiapo/C.Palanca 9,777 9,262 0 0 61 0 2,804 2,117 1,084 1,103 679 0 35 South Port Area 6,076 5,880 0 0 77 166 1,967 3,624 1,572 0 653 67 19,71 36 Intramuros/Muralla 5,993 40,053 53 1,078 119 1,427 2,530 14,645 827 291 163 0 Intramuros/Arrocer 33,19 37 3,059 65,279 0 851 75 2,120 1,182 25,810 217 849 268 os 3 38 Intramuros/Tanque 4,177 11,735 42 799 257 1,274 1,317 2,953 482 408 510 4,458 39 Ermita 4,407 35,660 0 372 0 2,139 1,695 29,608 543 111 484 1,104 40 Paco/Apacible 11,841 22,465 0 420 276 1,069 4,774 9,995 1,619 3,337 1,421 3,244 41 Paco/Canociga 24,385 26,248 210 205 1,217 649 6,933 4,943 2,045 3,424 2,234 3,341 42 Paco/Linao (Dart) 8,253 7,087 43 504 0 0 3,628 3,108 899 0 721 0 43 Malate/PCU 7,129 13,598 503 459 94 172 2,369 3,982 365 2,626 889 2,832 44 Malate/J.C.Bocobo 14,180 33,921 49 453 355 1,077 5,540 17,528 1,009 6,332 2,174 2,439 Malate/Harrison 45 17,782 23,840 0 403 815 1,783 6,738 11,755 2,190 154 1,384 1,939 Plaza San 46 40,349 34,508 117 631 2,520 1,019 13,980 10,602 2,587 570 4,579 2,069 Andres/L.Guinto 47 San Andres/SSH 17,200 14,415 70 20 922 694 7,280 5,628 704 0 1,503 187 San 48 27,424 21,040 164 39 2,147 490 9,071 7,397 2,963 317 2,003 29 Andres/Diamante 49 Paco/Fabie 20,002 22,842 50 38 739 493 4,715 4,723 1,560 3,808 1,986 827 50 Sta.Ana/Estrada 72,285 58,699 196 120 2,161 973 23,377 12,788 4,778 736 5,943 2,049 San 51 Miguel/Malacanan 10,063 13,114 0 109 384 922 2,362 4,032 661 237 1,425 1,677 g 52 Pandacan/Beata 50,038 44,264 720 532 1,932 793 18,497 11,946 2,589 3,256 3,580 991 Pandacan/T.Claudi 53 25,169 19,394 116 137 892 457 7,773 3,214 3,257 1,329 2,767 2,193 o Sta.Ana/Panadero 54 20,082 24,314 184 320 842 962 6,033 5,315 2,108 5,806 1,956 1,173 s Manila Noth 55 0 0 0000000 0 0 0 Harbour 56 MICT 0 0 0000000 0 0 0 57 BASECO 60,348 53,533 837 586 3,372 1,627 17,477 12,151 7,096 6,816 6,486 2,833 58 San Jose 26,662 30,112 490 1,142 396 886 4,315 5,258 2,537 4,518 2,716 383 59 San Isidro 21,280 19,063 120 268 496 540 6,310 3,575 2,342 1,999 1,812 998 60 Sta.Clara/Leveriza 21,977 23,816 151 333 294 601 4,288 6,340 3,027 1,158 2,361 2,133 61 Sta.Clara/Tramo 25,561 31,308 820 407 952 649 5,657 6,017 2,900 5,175 2,939 5,411 10,11 62 San Rafael 24,701 48,078 359 1,418 345 1,797 7,276 16,624 4,236 6,631 2,532 9 63 San Roque 47,541 44,688 219 69 839 1,055 12,173 9,368 6,244 6,125 3,439 1,028 64 Tabon 29,004 27,750 78 214 1,111 505 8,224 10,047 3,707 207 1,545 784 65 Malibay 76,578 78,200 1,099 1,268 2,590 1,693 20,966 16,516 11,203 14,143 5,865 6,032 66 Maricaban 59,194 51,157 396 524 1,724 962 14,441 11,311 8,364 6,116 5,255 300 67 Sto.Nino(Pasay) 29,248 21,897 450 161 603 558 7,667 4,475 2,912 397 2,887 94 68 Villamore Air Base 26,073 36,677 349 499 0 965 4,195 5,594 1,449 4,854 2,709 5,518 69 Air Cargo 24,222 28,155 1,390 671 878 445 5,924 4,295 2,959 7,123 2,263 3,399 70 Domestic Airport 4,527 5,265 342 78 70 146 1,280 2,134 336 93 415 505 PICC(reclamation 71 1,502 16,395 3781,744 0 2,445 42 11,188 329 0 0 81 area) CITE(reclamation 72 2,147 26,020 119 1,395 101 3,431 658 20,417 806 127 0 29 area) 73 Bangkal 28,313 37,686 387 437 763 2,303 5,689 9,218 4,234 5,582 2,413 4,096 74 Palanan 26,001 37,562 1,185 324 609 1,910 4,481 14,696 2,330 3,014 3,090 2,164 75 Pio Del Pilar 40,418 57,652 481 1,210 449 2,992 11,661 21,970 6,055 7,419 3,770 4,235 76 Tejeros 35,617 32,617 409 206 1,255 1,377 8,652 6,513 4,505 5,558 1,910 281 77 Olympia 35,367 42,595 47 511 1,003 2,214 8,153 11,989 4,110 6,751 3,927 1,874 78 Poblacion(Makati) 24,880 44,514 388 1,195 625 4,328 8,500 18,788 3,285 2,867 2,015 6,215 79 Legaspi Village 4,957 21,125 0 1,342 0 2,187 1,584 13,892 0 0 431 477 80 San Lorenzo 3,223 38,119 0 1,762 0 4,537 744 26,840 0 0 533 2,055

B-8

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 81 Ayala Center 0 29,746 0 1,082 0 3,711 0 24,485 0 0 0 0 82 Salcedo Village 6,389 28,144 0 3,294 0 2,183 4,372 19,810 0 0 0 592 83 Bel-Air II 1,938 8,107 0 235 0 598 1,059 5,559 0 128 0 654 84 Urdaneta 2,555 30,892 0 1,039 0 3,458 385 23,809 66 0 0 108 85 Bel-Air I 5,620 23,762 2081,422 0 1,595 3,055 17,991 0 0 0 0 86 Guadalupe Viejo 21,332 24,433 114 870 573 1,371 4,982 6,721 4,045 4,191 1,535 830 87 Guadalupe Nuevo 41,378 52,506 1,427 879 929 1,459 9,292 17,558 5,884 6,583 3,138 4,284 88 Cembo 48,600 39,355 430 102 743 578 13,175 6,685 4,663 6,122 5,993 869 Post Proper 89 8,144 4,135 735 99 0 0 1,836 511 1,462 412 1,173 0 Northside 18,69 90 Rembo 64,416 68,780 846 311 2,955 1,171 14,516 6,581 8,051 9,434 7,355 2 91 Pembo 166,682 138,958 2,150 1,262 2,809 1,806 38,196 18,619 23,231 21,307 15,085 6,389 92 Fort Bonifacio 27,421 90,326 1,074 3,324 884 13,306 3,524 51,014 3,954 2,938 2,257 3,786 93 Pinagsama 27,975 32,056 1,189 757 570 990 3,440 5,497 1,839 3,663 1,088 1,514 94 Dasmarinas/Forbs 5,669 10,579 0 907 0 1,266 1,803 4,420 351 774 591 0 95 Magallanes 4,501 15,794 0 257 0 1,572 1,787 11,289 380 0 805 949 96 Plainview 61,339 73,842 464 1,698 1,248 1,860 12,339 15,177 5,085 6,496 5,158 5,864 97 Old Zaniga 30,015 29,541 350 40 535 857 6,332 3,406 1,131 680 926 933 Poblacion(Mandal 98 38,602 44,755 97 398 1,402 782 10,730 13,075 4,782 5,493 4,333 5,043 uyong) 11,84 99 Hagdang Bato 34,140 49,954 519 288 534 1,570 7,816 8,038 2,931 6,400 2,729 5 100 Addition Hills 102,195 103,196 2,543 1,870 3,396 1,148 14,554 12,063 13,275 14,010 7,776 5,280 101 Barangka 35,045 53,380 524 1,073 1,471 3,310 8,571 17,996 2,946 1,896 3,734 9,004 102 Highway Hills 59,514 88,984 746 1,628 1,565 3,968 14,862 33,841 6,314 7,501 5,149 7,137 Wack- 103 10,150 61,896 0 3,996 0 9,427 0 46,440 0 0 0 736 Wack/Greenhills 104 Ortigas Center 0 16,192 0 816 0 2,834 0 12,437 0 0 0 0 105 East Greenhills 2,182 7,286 0 0 0 641 0 6,372 0 0 0 273 Greenhills Com'l 106 8,343 18,340 0 106 0 1,256 3,200 10,494 0 344 560 302 Center 107 West Crame 15,922 13,426 333 227 0 86 3,640 1,476 1,497 840 1,145 0 108 Batis 52,444 46,364 899 129 1,282 1,019 10,870 5,163 4,797 4,041 4,454 890 109 Corazon De Jesus 45,609 57,627 362 772 472 936 9,273 10,792 3,368 6,874 2,946 4,311 110 Dona Imelda 33,677 43,989 889 964 1,023 1,893 9,633 12,953 3,446 4,980 2,769 6,023 111 Santo Nino 33,124 36,899 221 106 1,161 570 9,147 9,820 2,302 4,857 2,007 2,548 112 Tatalon 73,911 64,464 1,191 1,163 2,506 1,501 14,359 10,280 8,832 6,591 5,776 1,878 113 Santa Teresita 23,855 31,487 388 359 732 1,514 6,560 12,832 2,075 2,329 493 122 N.S.Amoranto(Gint 114 28,795 28,589 761 1,037 919 913 6,289 5,632 2,784 1,330 2,323 3,034 ong Silahis) 115 Manresa 40,988 35,810 503 251 623 1,492 9,352 9,093 6,658 2,221 3,001 1,119 116 Balingasa 32,539 34,685 3,704 3,647 1,976 2,015 7,304 11,021 1,826 2,463 3,908 1,115 117 Apolonio Samson 44,263 53,633 767 1,048 1,381 2,035 7,900 16,085 3,106 3,822 2,263 451 118 Masambong 21,382 26,376 575 851 1,081 753 5,779 4,956 1,761 4,471 1,006 3,831 Santo 119 Domingo(Matalahi 15,911 19,260 250 896 643 1,309 4,716 8,664 1,963 68 547 547 b) 120 Del Monte 62,562 70,665 1,078 1,343 2,495 5,885 15,949 18,021 6,741 8,496 4,101 3,599 121 San Antonio 28,593 22,970 540 514 959 905 8,096 6,163 4,139 2,255 2,716 350 122 Veterans Village 25,839 35,221 1,136 1,183 529 2,023 4,955 9,886 4,680 6,798 2,169 2,275 123 Phil-Am 8,871 12,714 0 446 854 1,439 3,238 6,512 1,236 871 458 78 124 South Triangle 14,364 36,138 98 1,828 98 3,728 2,834 19,972 1,388 488 607 311 125 Kamuning 30,800 45,206 1,004 1,512 536 2,518 9,006 14,788 2,434 7,014 2,581 3,705 126 Roxas 35,965 40,418 1,188 1,222 722 997 9,996 12,179 4,094 3,463 2,295 3,700 127 Kalusugan 23,048 21,619 563 280 670 550 6,459 8,237 3,619 604 1,783 1,561 128 Mariana 17,968 20,154 124 521 1,227 1,345 2,037 4,395 1,728 487 526 315 129 Kaunlaran 23,669 27,989 1,311 498 617 1,414 4,834 7,496 1,831 3,284 2,822 2,749 Immaculate 130 18,042 19,080 168 326 209 769 4,960 2,613 987 778 1,887 4,414 Concepcion Bagong Lipunan 131 24,377 25,656 596 556 550 1,209 5,653 9,224 2,738 1,186 2,912 1,072 Crame 132 Crame 5,530 1,980 0 00001,5320 286 0 268 133 Ugong Norte 12,303 2,953 0 134 0 346 0 1,736 0 0 0 666 134 Camp Aguinaldo 6,122 13,154 0 0 0 563 1,529 5,712 504 580 383 2,352 135 White Plains 17,130 26,281 0 1,314 711 3,034 5,264 11,950 2,929 2,587 1,607 490 136 Murphy District 23,807 83,925 104 2,967 2,124 10,692 6,958 51,453 3,465 1,178 1,199 5,876 Cubao(Araneta 137 0 7,755 0 587 0 3,159 0 4,009 0 0 0 0 Center)

B-9

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 138 E. Rodriguez 27,914 44,750 735 905 425 2,175 7,234 14,445 2,490 4,854 2,025 6,756 16,12 139 San Roque 67,406 84,769 1,346 1,002 1,178 2,849 15,808 13,088 6,629 12,422 5,315 7 140 Escopa 25,900 37,448 69 2,380 742 3,193 6,520 16,938 1,948 331 3,167 551 141 Quirino 3 16,380 19,884 103 245 447 465 4,734 4,496 1,640 2,541 970 3,493 142 Quirino 2 28,454 34,755 539 1,266 480 1,396 7,365 7,914 1,958 4,928 2,801 3,028 143 Loyola Heights 66,852 60,979 490 699 1,809 1,609 17,652 13,346 7,278 6,556 5,995 4,064 144 Teachers Village 22,376 21,259 868 684 0 1,195 7,309 7,815 1,757 508 2,127 432 145 QMC 74,059 112,372 1,903 5,229 1,475 4,225 21,229 53,664 4,389 5,145 7,046 4,954 146 U.P. Campus 68,540 71,073 1,794 1,943 1,385 1,490 21,536 23,173 5,124 2,681 5,602 6,865 15,43 147 Batasan Hills 177,227 164,530 5,827 3,394 7,110 4,731 44,459 30,422 20,164 23,414 16,322 6 148 Matandang Balara 83,808 70,624 3,401 1,306 3,934 2,798 20,680 15,264 8,439 5,526 6,076 3,513 149 Holy Spirit 113,948 101,954 3,465 2,708 6,777 2,418 25,983 16,314 11,024 15,229 8,635 6,034 150 Payatas 140,279 108,586 3,989 1,815 5,723 2,334 35,262 15,529 18,115 17,748 13,461 4,800 151 Bagong Silangan 0 0 0 000000 0 0 0 152 Constitution Hills 95,252 75,923 999 95 5,209 2,047 24,593 10,627 9,879 9,491 9,288 6,730 25,02 153 Commonwealth 236,615 249,443 6,409 5,770 6,997 7,760 59,484 56,587 28,327 32,750 19,856 9 154 Fairview 56,156 64,957 1,695 1,338 2,437 2,601 14,574 18,320 6,432 6,716 4,895 9,731 33,44 155 Pasong Putik 111,012 172,205 2,907 5,455 5,494 6,814 22,440 50,667 11,879 15,171 12,147 4 14,47 156 Kaligayahan 112,203 105,798 3,178 1,734 5,373 3,423 22,921 18,421 15,321 14,011 13,602 2 14,15 157 San Agustin 110,834 144,415 2,187 2,737 4,853 10,797 24,732 43,401 14,851 14,785 8,699 7 19,74 158 Gulod 140,761 144,666 4,433 2,961 5,300 3,710 29,290 24,791 15,610 18,448 13,748 9 159 Sauyo 93,806 74,939 1,358 321 2,702 2,511 22,729 8,400 9,005 7,960 9,101 4,564 160 Bagbag 48,694 42,090 532 230 3,219 2,370 10,057 7,339 5,988 5,913 4,775 1,324 11,03 161 Tandang Sora 149,862 153,509 4,241 2,882 5,288 4,508 31,609 34,184 15,074 17,109 13,125 5 162 Pasong Tamo 103,263 79,248 2,240 960 3,761 1,232 27,135 15,637 11,951 10,010 7,850 581 163 Culiat 80,330 71,519 1,503 631 3,609 892 17,932 12,910 10,474 9,583 6,967 5,832 164 Project 6 78,373 129,532 1,068 4,368 1,307 5,680 18,715 57,734 7,696 7,414 5,762 7,694 Ramon 165 38,303 51,818 634 1,278 769 1,883 7,876 12,934 2,669 3,760 4,487 8,591 Magsaysay 166 Bahay Toro 88,153 85,826 1,882 1,404 4,363 5,042 25,978 25,122 9,290 8,294 5,228 3,413 167 Baesa 81,494 69,202 562 1,130 4,081 3,808 18,886 11,631 9,937 9,233 7,222 2,088 168 Sangandaan 28,312 32,523 1,061 787 1,235 958 4,932 5,282 2,953 4,608 3,295 4,709 169 Bo. San Jose 28,926 22,918 1,171 541 590 280 9,160 6,754 3,937 2,894 2,837 185 170 West 3/4 Ave. 36,487 32,292 778 485 837 1,332 7,178 5,763 4,197 2,866 3,995 1,075 171 A.Mabini 150,435 126,610 1,700 643 3,623 1,710 34,742 18,741 19,901 16,552 11,506 3,772 172 Dagat Dagatan 127,444 117,693 2,974 1,802 4,275 3,530 27,134 20,546 16,944 17,537 11,914 4,748 14,97 173 West 8/10 Ave. 70,449 93,843 1,401 2,614 1,559 2,857 16,437 26,155 8,557 10,133 8,628 1 174 Grace Park 54,711 70,852 681 1,397 1,094 2,958 13,574 19,657 7,613 8,510 5,181 9,454 12,15 175 Sangandaan 20,623 40,443 0 696 138 1,738 3,880 9,319 1,270 1,171 1,026 2 Bagon Barrio 176 19,995 34,272 305 1,484 305 1,844 7,440 11,552 1,567 4,220 807 4,789 EDSA Bagon Barrio 177 84,666 70,267 1,545 233 4,659 1,874 17,388 9,783 10,742 8,331 7,842 3,945 Center 178 Bagon Barrio East 87,418 81,137 1,759 951 3,081 2,268 17,060 11,587 11,975 13,039 8,164 5,413 13,47 179 Bagumbong 1(CN) 137,378 129,935 1,239 1,016 7,390 4,141 26,382 18,281 19,704 18,279 13,667 3 180 Bagumbong 2(CN) 94,617 99,420 1,479 850 3,694 4,380 18,830 18,097 11,262 14,483 8,095 5,798 181 Bagumbong 3(CN) 51,320 50,567 1,508 770 2,424 1,795 9,135 5,547 8,697 11,058 5,493 5,293 17,98 182 Camarin 1(CN) 100,539 103,734 1,151 978 5,253 3,755 28,160 21,142 12,081 14,591 12,216 3 10,33 183 Camarin 2(CN) 207,616 197,299 1,563 1,199 7,251 1,705 38,097 25,569 24,688 27,313 14,880 6 20,80 184 North 1(CN) 287,022 268,144 2,438 1,695 12,544 4,815 53,499 31,562 38,535 42,166 25,873 6 185 West(CN) 188,820 168,510 4,411 3,086 9,818 3,130 40,950 22,940 23,264 23,067 18,867 17,111 186 Canumay 104,242 105,056 1,206 1,173 6,471 7,971 23,442 19,942 15,556 14,783 8,807 8,337 Mapulang 187 86,460 85,660 4,120 4,138 4,464 4,707 13,497 9,269 10,867 10,555 9,027 8,690 Lupa/Ugong 188 Bagbaguin 30,104 39,878 746 907 1,497 3,214 6,599 12,889 3,095 4,707 2,290 958

B-10

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 189 Hen. T. De Leon 94,597 87,171 3,324 1,730 3,344 1,119 17,031 8,978 12,760 13,115 7,060 6,659 10,67 190 Marulas 56,175 71,562 104 227 545 1,716 6,513 7,228 3,778 5,655 2,842 5 11,32 191 Karuhatan 95,739 131,115 1,253 1,929 1,757 6,127 14,326 31,452 5,991 8,734 6,708 5 192 Maysan 72,257 62,143 1,429 1,148 5,219 3,686 15,279 10,383 6,581 6,869 9,179 2,714 Malanday(Valenzu 193 52,588 53,435 899 1,388 958 1,109 8,628 8,089 5,141 5,145 3,107 1,241 ela) 10,90 194 Dalandanan 59,337 72,505 235 691 3,782 4,899 11,647 13,677 9,828 11,274 5,168 7 195 Maysilo/Panghulo 45,382 43,063 601 286 2,529 1,170 9,501 6,243 5,064 5,852 3,844 2,174 196 Potrero 40,780 45,844 831 627 1,922 3,555 3,995 4,244 5,911 7,035 3,383 1,846 197 Tugatog 48,516 58,068 413 332 1,431 2,934 14,760 12,740 5,381 9,499 3,554 6,058 198 Longos 62,314 76,792 1,079 1,984 1,445 1,111 10,743 11,168 6,258 8,671 3,591 8,240 199 Tonsuya 84,998 83,039 1,732 710 2,222 1,270 15,539 13,720 8,759 7,622 5,613 950 Baritan/Concepcio 200 65,348 78,781 1,469 2,055 1,246 1,029 12,797 14,479 7,444 11,532 7,839 9,442 n 201 Dampalit 17,164 14,829 549 374 1,554 1,421 3,758 2,390 2,410 1,444 601 0 202 Tanza 27,013 23,203 1,059 401 1,040 185 6,479 3,833 4,379 3,718 2,429 1,535 203 Tangos 52,792 54,605 3,549 2,421 1,122 838 7,397 6,112 6,130 6,787 2,648 1,278 204 San Jose 62,540 77,854 542 1,040 895 1,465 7,566 9,942 3,800 6,764 2,466 3,949 205 Navotas East/West 44,687 47,798 852 707 1,091 1,572 3,969 3,891 4,507 3,334 1,438 95 206 North Bay Blvd. 76,468 85,388 2,068 4,190 2,608 3,019 11,625 11,307 7,984 8,703 7,271 6,120 207 Navotas Fishport 0 0 0 000000 0 0 0 208 Nangka 42,310 40,031 527 744 2,465 1,362 12,435 8,617 6,155 7,070 3,365 2,784 209 Parang 76,307 91,705 422 360 2,919 4,615 6,915 8,643 2,763 5,477 3,708 4,235 Concepcion(Mariki 12,93 210 86,881 97,635 1,272 846 4,221 2,572 18,697 19,059 8,587 10,093 8,585 na) 6 211 Marikina Heights 62,115 65,289 648 591 1,866 1,448 12,945 12,633 5,017 4,547 5,308 4,238 Calumpang/San 13,65 212 41,507 81,583 702 842 1,210 4,696 9,807 29,931 3,433 7,976 5,300 Roque 9 213 Santo Nino 28,896 38,439 705 706 1,223 3,161 8,665 13,402 3,217 3,994 2,224 2,214 Malanday(Marikina 214 55,561 55,701 684 786 2,345 705 10,083 7,247 3,379 3,705 2,901 1,824 ) Barangka(Marikina 215 56,424 62,349 379 201 1,276 1,696 11,796 12,870 4,418 5,620 4,329 2,752 ) 216 Kalawaan 63,787 61,065 976 536 1,928 2,239 8,595 6,894 5,965 7,433 4,739 3,281 Santolan/Manggah 15,29 217 207,440 220,568 4,538 4,084 7,451 15,828 41,831 53,048 23,841 21,322 17,418 an 7 218 Santa Lucia 52,902 53,007 672 211 1,076 1,364 8,908 6,822 5,215 7,117 3,994 4,970 219 Maybunga 41,212 47,428 374 877 2,101 3,381 6,426 6,596 2,122 4,581 3,070 5,307 220 Ugong 25,801 40,426 1,440 1,543 604 3,752 4,041 17,644 2,937 3,226 2,959 541 221 San Antonio 25,285 64,893 99 2,197 99 5,384 3,049 34,704 1,114 1,404 942 975 222 Kapitolyo 41,232 41,003 788 1,152 1,698 1,875 11,303 11,941 3,863 3,316 4,409 3,944 223 Bagong Ilog 20,634 19,193 75 444 828 1,281 3,806 4,138 2,499 1,725 1,713 78 224 Bambang 88,045 109,035 1,646 1,734 2,647 4,653 12,880 24,839 6,176 10,665 4,851 8,049 12,76 225 Caniogan 79,530 83,877 1,423 1,824 1,944 2,095 16,188 11,660 7,175 9,191 5,953 8 226 Pinagbuhatan 178,632 150,899 2,440 1,964 5,681 2,841 29,695 17,011 17,504 13,956 13,467 7,381 Santa 227 69,500 76,966 3,132 2,560 2,236 1,078 18,117 17,837 6,988 8,764 7,152 9,603 Ana(Pateros) 228 Bagumbayan 107,653 99,554 1,242 1,091 5,300 4,713 19,988 13,967 14,928 16,853 7,662 4,688 26,99 229 Bicutan 202,128 191,460 3,317 2,798 8,189 6,958 43,561 33,991 27,657 23,746 22,353 5 230 Signal Village 89,431 88,195 413 259 939 393 11,650 9,010 4,988 7,395 5,014 5,327 231 Western Bicutan 86,400 84,853 1,223 902 4,703 3,166 11,058 12,642 11,967 12,217 8,352 7,076 232 Hagonoy 111,596 93,448 1,106 949 1,984 1,043 14,869 6,253 8,599 6,551 7,246 1,178 14,90 233 Ususan 165,396 149,604 4,264 3,244 9,876 6,460 36,118 27,906 22,747 22,339 17,133 2 234 Baclaran 21,142 46,710 415 498 647 2,203 6,624 23,776 2,495 6,031 2,834 5,472 235 Tambo 31,082 38,684 214 900 1,109 2,805 5,083 11,228 4,799 4,338 1,897 593 236 La Huerta 11,708 19,599 221 95 0 113 2,861 5,424 2,117 4,065 1,023 4,164 15,29 237 San Dionisio 71,211 86,610 1,288 2,416 1,004 2,174 20,912 22,071 8,727 12,300 8,993 3 238 Moonwalk 79,209 72,295 1,647 1,118 4,510 3,185 18,762 11,909 10,520 10,547 7,180 7,419 Santo 239 38,720 42,758 798 995 1,609 1,311 10,029 14,349 5,210 4,607 2,248 1,580 Nino(Paranaque) 240 Merville 26,943 19,720 1,508 851 1,750 1,462 4,445 4,035 3,886 159 2,486 0 241 Sun Valley 67,644 68,564 1,259 1,009 2,418 2,741 18,482 17,505 8,639 7,783 5,868 7,124

B-11

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 242 Don Bosco 60,242 72,358 576 1,498 3,026 4,034 14,297 22,223 11,371 15,005 5,108 2,287 Marcelo Green 243 33,889 25,581 0 124 2,061 1,441 7,485 5,659 4,487 102 1,660 0 Village 244 San Antonio 73,104 82,543 1,972 543 2,023 2,606 8,648 14,240 7,587 11,715 4,878 3,245 245 San Isidro 88,394 71,880 1,637 354 2,221 1,689 19,356 15,131 16,509 8,641 8,126 3,626 246 B.F.Homes 30,877 27,922 153 298 1,556 1,106 5,703 4,178 2,618 1,370 1,306 671 247 B.F.Homes 57,073 57,700 1,637 1,437 480 2,388 15,394 15,299 6,402 6,159 3,284 1,059 248 B.F.Homes 11,475 11,539 261 185 131 146 2,280 2,867 1,436 1,201 679 144 249 NAIA 2,784 4,895 0 0 0 0 696 791 512 2,186 156 344 Marina Manila 250 14,287 14,104 224 339 579 772 2,355 891 2,639 2,644 1,100 1,974 Baytown 251 Sucat 59,532 68,869 472 1,069 2,523 3,738 9,623 11,875 4,728 5,039 6,199 8,298 252 Cupang 63,194 55,261 770 849 1,867 3,393 11,480 5,107 7,837 5,172 4,266 1,031 11,74 253 Alabang 107,541 180,896 1,731 3,991 4,107 11,341 19,920 66,179 11,518 18,931 6,965 0 New Alabang 254 24,487 17,131 2,787 649 421 317 7,038 3,447 1,793 563 1,123 121 Village 255 Putatan 93,067 89,004 2,070 1,176 3,881 3,141 19,109 16,160 12,331 13,906 8,056 4,338 Poblacion 20,83 256 124,823 127,178 1,698 1,955 3,527 1,547 28,605 19,237 13,694 14,561 12,441 (Muntinlupa) 2 257 Tunasan 57,356 65,002 1,579 1,742 3,148 4,012 11,136 17,395 8,469 7,995 4,030 2,894 258 Manuyo 59,077 58,239 217 373 2,628 1,807 14,825 11,537 8,040 7,257 4,972 5,990 Elias 259 Aldana/Daniel 29,690 28,488 301 563 1,401 558 7,476 4,368 3,775 4,721 2,098 2,323 Fajardo 260 Pulang Lupa 65,325 64,832 666 1,450 2,970 4,353 17,685 15,953 8,880 7,662 5,251 2,114 14,79 261 Pamplona 101,552 123,066 2,788 2,414 4,744 6,651 21,338 20,895 11,219 17,302 6,867 1 262 B.F.International 105,182 107,533 1,977 1,045 4,522 4,360 25,146 17,211 14,704 18,496 7,443 9,015 263 Talon 106,348 114,129 1,704 2,021 5,665 4,646 20,907 19,696 16,421 19,164 7,838 8,350 264 Pilar 76,105 73,308 1,093 725 4,020 2,533 16,801 13,426 12,688 12,614 4,927 3,671 265 Almanza 76,721 92,835 1,474 2,092 2,608 2,639 8,769 15,729 8,416 11,163 5,662 5,904 266 Obando 64,000 66,074 2,018 2,010 2,656 1,917 14,500 14,606 10,189 11,097 4,721 2,684 267 Marilao(West) 109,814 82,765 922 1,412 6,420 5,441 26,586 21,506 23,801 16,099 10,051 9,414 Meycauayan(West 11,83 268 151,737 146,742 1,699 1,385 8,185 7,461 37,505 33,856 26,950 27,472 11,840 ) 6 23,40 269 SJDM(West) 279,521 217,931 8,225 8,069 12,104 12,624 76,737 42,060 26,246 21,926 23,953 8 270 Norzagaray 142,500 115,828 6,552 6,072 8,338 5,967 21,469 14,529 26,124 23,652 13,822 8,357 11,63 271 Santa Maria(West) 115,459 110,767 1,668 1,850 8,636 8,776 32,093 34,455 18,690 17,309 8,821 0 11,72 272 Bocaue 133,000 130,612 3,663 4,187 8,400 8,650 28,041 27,596 28,373 28,074 12,773 0 273 Bulacan 83,500 80,701 4,681 5,108 5,405 4,224 21,684 20,526 11,187 11,359 6,576 4,179 274 Balagtas 76,000 89,016 2,172 1,955 4,101 5,183 17,119 24,440 12,983 13,196 5,766 7,725 275 Pandi 95,500 82,445 4,398 3,703 3,724 1,967 20,606 15,621 12,993 12,119 6,137 5,650 276 Guiguinto 125,000 111,832 1,930 1,828 7,819 7,600 36,329 33,282 16,014 14,517 12,462 8,895 277 Plaridel 131,000 118,545 1,671 1,721 3,926 2,874 37,355 33,775 28,030 26,598 11,349 7,356 278 Pulilan 110,500 98,159 2,989 2,834 9,581 7,553 29,915 24,972 6,752 6,761 10,072 7,014 38,07 279 Malolos(North) 153,497 164,549 5,089 5,175 4,080 4,921 35,891 34,240 24,551 20,706 16,307 3 280 Paombong 64,000 53,225 4,915 4,597 2,602 932 13,870 9,928 10,345 9,876 6,017 3,406 281 Hagonoy 143,000 137,309 6,205 5,542 3,443 1,877 31,940 26,243 24,680 26,301 11,760 8,931 282 Calumpit 128,500 118,160 1,917 1,622 5,162 5,010 33,120 30,391 15,599 14,645 8,496 3,617 Gen. Mariano 10,17 283 166,500 150,849 2,646 2,123 11,256 6,190 51,290 40,807 19,476 19,090 10,607 Alvarez 6 14,84 284 Dasmarinas(West) 135,879 146,475 3,764 4,295 12,797 9,055 45,919 52,996 14,519 20,378 6,979 2 285 Bacoor(North) 108,719 85,896 2,438 1,158 4,164 4,695 28,840 21,816 14,014 11,783 6,363 1,342 286 Imus(North) 137,990 149,328 1,612 1,329 12,940 14,875 41,856 48,306 8,042 11,434 5,026 8,531 287 Kawit 95,000 89,073 2,210 1,761 8,057 5,484 25,419 23,659 14,149 13,227 7,499 6,743 288 Cavite City 102,500 109,692 2,329 1,738 5,568 3,216 36,001 36,809 5,350 6,692 7,525 8,131 289 Noveleta 52,500 46,671 587 420 2,304 605 14,999 12,939 6,667 5,261 4,521 3,918 290 Rosario 112,000 176,966 5,439 7,965 12,765 42,891 36,037 62,243 7,126 8,164 4,325 8,570 General 291 189,103 108,258 6,805 3,514 24,819 11,700 61,854 32,354 13,291 7,892 5,575 4,075 Trias(North) 292 Tanza(North) 155,005 115,504 6,847 5,065 12,648 3,379 52,228 37,747 6,350 7,235 5,491 4,096 293 Trece Martires 238,500 131,301 2,812 2,532 25,153 12,615 69,159 32,544 30,246 18,129 16,028 9,498 294 Naic 104,000 101,121 6,809 6,260 4,775 2,240 24,547 22,856 17,910 18,603 6,389 5,841

B-12

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 295 Silang(West) 117,852 112,987 3,519 2,766 10,890 8,573 30,295 27,177 22,194 22,704 6,807 8,696 296 Carmona 111,000 106,419 2,988 3,484 10,906 11,409 29,508 32,371 14,518 12,644 7,498 6,449 17,91 297 San Pedro(North) 177,637 174,324 1,458 1,070 8,794 6,781 45,337 33,793 24,580 25,821 15,986 7 24,30 298 Binan(North) 214,596 236,679 8,136 8,119 9,115 6,998 46,033 53,163 31,529 38,525 20,254 5 Santa 23,54 299 294,104 295,076 7,856 7,912 20,034 16,351 66,258 70,834 39,264 37,799 22,056 Rosa(Center) 2 300 Cabuyao(North) 169,914 136,395 4,540 3,338 10,419 8,370 38,317 26,332 24,621 21,061 13,242 9,855 City of 16,19 301 217,171 225,363 8,958 8,661 8,856 6,235 38,893 38,417 33,962 36,190 14,274 Calamba(Center) 3 11,90 302 Los Banos 115,000 125,234 3,729 3,790 3,310 2,523 25,669 26,447 16,238 17,888 9,102 5 27,31 303 Taytay(West) 265,305 229,911 2,314 1,272 14,245 11,850 61,300 41,569 27,771 26,213 35,361 6 12,95 304 Cainta(South) 227,100 196,250 2,673 793 11,387 6,929 47,864 30,849 29,480 23,951 21,374 3 10,41 32,47 305 Antipolo(Center) 343,717 323,978 9,289 22,547 19,716 71,792 54,995 44,444 48,094 31,790 8 2 306 San Mateo(South) 177,858 153,358 2,194 1,226 9,219 6,444 36,617 26,315 18,883 17,325 12,126 7,034 18,13 307 Rodriguez(West) 279,260 188,894 1,777 1,423 15,848 7,057 61,413 32,264 33,772 27,497 26,799 7 17,29 308 Angono 129,500 117,384 2,336 2,040 8,221 5,399 30,935 23,527 13,772 13,581 18,921 8 21,22 21,23 17,61 309 Binangonan(North) 277,042 254,355 14,650 11,146 61,969 46,262 36,092 36,414 22,285 4 5 7 310 Cardona 55,000 51,925 3,269 2,620 3,025 2,159 10,892 8,470 5,624 5,817 5,605 4,028 13,16 311 Morong 60,500 68,010 2,902 1,618 3,039 2,742 13,914 12,749 11,724 12,792 5,653 3 312 Teresa 66,000 53,865 1,752 1,937 3,473 3,207 18,712 14,478 7,382 6,830 6,796 1,964 313 Baras 40,500 36,215 730 836 2,905 1,853 11,830 9,973 3,578 3,592 4,819 3,261 12,86 314 Tanay 117,500 122,821 5,752 5,690 7,770 7,659 21,997 22,794 18,025 19,239 12,515 3 315 Pililia 73,000 69,274 5,381 5,276 3,212 2,664 11,426 8,414 10,581 10,621 7,812 7,861 316 Jalajala 36,000 34,908 2,651 2,779 1,371 875 7,739 7,056 5,701 5,991 3,501 2,545 317 North 2(CN) 21,532 18,208 0 590 1,338 498 4,984 2,721 2,346 2,867 2,530 460 Manila Harbour 318 0 0 0000000 0 0 0 Center Manila South 319 0 0 0000000 0 0 0 Harbour 320 NAIA Terminal 1 0 5,379 0 443 0 592 0 4,344 0 0 0 0 321 NAIA Terminal 2 0 1,990 0 433 0 0 0 1,557 0 0 0 0 322 NAIA Terminal 3 0 2,933 0 0 0 330 0 2,604 0 0 0 0 NAIA Domestic 323 0 1,183 0 00001,1830 0 0 0 Terminal 12,78 324 Marilao(East) 260,186 158,413 2,775 1,261 25,471 12,809 44,989 23,788 50,490 33,133 25,956 7 325 Meycauayan(East) 96,263 92,070 1,272 1,510 8,646 11,607 20,652 19,756 21,061 19,680 8,390 4,199 326 SJDM(East) 135,705 103,391 1,932 1,951 8,509 5,095 30,593 21,201 19,490 16,087 13,388 8,520 10,73 14,36 327 SJDM(North) 268,274 185,012 5,409 19,223 6,113 55,589 30,244 43,030 34,017 24,520 2 5 11,15 328 Santa Maria(West) 232,041 168,826 4,130 2,671 9,751 6,386 60,562 40,796 41,202 30,824 20,143 4 14,68 329 Malolos(South) 172,503 160,927 7,367 7,269 7,707 5,867 48,059 46,509 26,361 26,340 16,674 9 Dasmarinas(Cente 110,27 10,95 330 341,460 246,875 3,059 237 27,596 14,741 68,375 32,469 21,200 15,984 r) 6 1 331 Dasmarinas(East) 187,972 127,071 2,639 1,407 22,703 8,673 43,963 18,672 17,825 14,017 12,917 8,611 Dasmarinas(South 332 163,688 188,630 3,485 4,849 19,312 36,172 53,955 69,335 16,906 16,508 9,174 8,530 ) 11,66 333 Bacoor (Coastal) 264,196 207,808 5,776 5,040 21,638 10,833 63,223 47,939 42,569 34,308 18,115 2 12,64 334 Bacoor(Center) 225,317 176,364 3,933 1,530 17,843 13,341 55,077 34,746 32,427 27,982 16,143 1 10,02 335 Bacoor(South) 232,767 183,435 2,890 876 19,013 14,767 55,094 37,873 34,717 29,151 14,887 0 336 Imus(Center) 175,341 174,706 2,840 2,471 13,435 17,944 45,730 53,268 15,761 13,102 14,388 8,572 337 Imus(South) 127,669 105,310 4,563 3,434 9,034 7,712 34,141 18,420 13,180 11,584 7,473 7,935 General 12,38 338 315,397 197,285 8,136 7,320 42,044 21,419 81,902 52,424 27,984 17,926 20,388 Trias(South) 2

B-13

Student Population Primary Secondary Tertiary Student (Elem.) Zone NAME (H.S. & Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 339 Tanza(South) 147,995 99,952 7,564 4,700 14,733 5,252 30,726 16,275 17,499 12,204 7,137 4,724 340 Silang(East) 162,148 138,164 6,672 6,258 11,562 9,625 50,281 36,203 17,653 16,780 12,931 8,405 11,48 341 San Pedro(South) 160,363 173,984 3,372 3,772 8,693 10,473 42,552 43,586 23,262 26,408 11,092 6 10,91 342 Binan(South) 130,404 141,812 1,723 2,127 8,203 18,130 37,113 40,262 17,493 14,745 13,318 5 343 Santa Rosa(West) 70,896 75,037 1,825 2,229 4,093 9,363 16,201 18,771 11,847 11,688 5,944 2,821 17,30 344 Cabuyao(South) 239,586 203,385 6,108 6,668 15,976 13,205 46,013 37,867 34,983 29,000 20,112 5 City of 11,45 345 190,212 200,817 3,499 3,556 13,409 14,719 32,749 33,735 26,512 28,102 11,183 Calamba(West) 8 City of 346 61,617 75,559 733 1,329 2,434 5,559 10,069 15,562 7,712 8,832 2,771 3,158 Calamba(East) 347 Taytay(East) 117,195 120,769 1,550 1,191 10,456 8,518 26,437 31,557 15,008 16,960 10,648 8,709 33,94 348 Cainta(North) 147,900 179,130 1,782 3,343 6,465 8,931 33,623 40,627 18,891 17,421 17,294 6 17,63 349 Antipolo(South) 221,660 208,886 2,595 3,797 12,147 10,187 44,100 38,202 28,303 30,563 23,064 6 11,62 350 Antipolo(North) 224,151 174,160 1,614 1,098 13,919 7,170 46,108 27,214 28,454 19,321 22,254 4 Antipolo 351 98,471 84,421 1,075 1,015 5,670 3,724 13,845 8,676 12,429 10,967 8,772 5,455 (North-East) 352 San Mateo(North) 101,642 85,865 2,477 1,083 5,064 2,334 20,260 13,765 11,558 10,869 7,057 4,308 12,90 353 Rodriguez(East) 274,740 176,328 3,147 1,895 16,717 8,625 47,941 22,256 42,522 28,331 23,550 5 Binangonan(South 354 31,958 28,808 5,821 4,754 1,436 867 4,640 3,533 2,600 2,248 2,772 2,084 ) Total 26,422,999 26,422,999 566,725 562,188 1,349,975 1,294,082 6,225,525 6,230,570 3,231,589 3,214,030 2,201,689 2,220,229

B-14

Table B-3: Population in 2035

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 163,20 1 Divisoria/Zaragosa 157,839 1,535 1,347 4,293 3,507 53,152 52,555 18,360 19,984 15,749 1,833 4 140,84 2 Tondo/Moriones 128,269 844 1,887 2,804 1,487 43,007 39,493 15,750 17,520 10,951 9,381 2 3 Tondo/Herbosa 104,979 118,979 349 1,608 3,578 3,560 35,802 32,672 11,594 16,961 10,657 8,239 4 Tondo/H.Lopez 49,676 60,064 282 456 1,532 3,060 15,597 18,050 6,555 8,223 5,395 3,844 107,22 5 Tondo/J.Luna 88,505 373 574 2,467 2,112 28,032 27,938 9,570 11,298 10,774 16,827 8 6 Tondo/Corregidor 35,803 42,403 0 209 2,331 1,511 11,164 10,413 3,549 7,063 3,004 2,711 La Loma/Chinese 7 20,725 22,949 76 208 781 1,887 7,742 8,631 1,621 1,017 1,959 63 Cemetery 8 Tondo/J.A.Santos 48,103 47,491 549 1,100 1,153 822 15,601 13,001 4,912 5,393 6,096 1,481 Sta.Cruz/J.A.Sant 9 63,921 87,705 83 408 1,342 2,745 25,559 38,097 5,490 11,780 7,567 3,428 os 10 Divisoria/Del Pan 26,053 60,009 201 830 1,189 2,107 9,197 23,477 1,582 8,389 2,085 9,624 11 Binondo/J.Luna 5,411 16,346 0 496 327 829 2,873 11,176 180 371 366 1,306 Binondo/Reina 12 8,988 31,719 0 539 114 3,344 3,029 21,313 1,456 299 923 1,600 Regente Binondo/Mesericor 13 5,775 13,468 44 227 81 527 2,075 8,403 148 0 995 1,008 dia 14 Quiapo/Carriedo 4,955 35,815 46 995 46 2,721 3,031 23,220 55 225 292 5,882 15 Sta.Cruz/D.Jose 20,945 27,930 0 0 295 1,015 7,120 8,580 2,658 419 2,786 6,569 16 Sta.Crus/Bambang 37,731 53,022 198 128 591 1,583 14,940 18,766 2,618 8,850 3,960 3,519 Sta.Cruz/San 17 36,453 67,756 390 577 873 2,955 14,546 33,646 3,429 7,714 3,768 5,577 Lazaro Quiapo/Globo de 18 10,965 15,958 76 143 63 316 4,181 4,292 1,097 443 1,527 5,336 Oro Quiapo/Bilibid 19 11,721 31,750 74 409 319 380 4,884 6,969 1,162 5,026 649 12,823 Viejo 20 Sampaloc/FEU/UE 12,901 52,191 52 314 672 1,086 4,204 6,043 1,477 3,345 1,234 33,716 Sta.Mesa/Lardizab 21 13,441 25,475 42 227 269 271 4,440 6,604 1,557 646 1,134 9,799 al Ext. Sta.Mesa/Peereza 22 20,569 19,352 182 297 428 511 7,856 4,446 1,395 843 1,810 1,679 Ext. 23 Sampaloc/NU 37,594 35,707 68 316 1,525 1,479 12,411 10,019 3,371 4,686 6,389 1,187 24 Sampaloc/UST 7,090 25,169 14 18 204 1,379 3,083 7,333 232 424 786 12,409 Sampaloc/Florenti 25 34,484 53,092 418 766 1,735 2,339 11,055 12,067 2,156 7,022 3,419 10,154 no Sampaloc/Calamb 26 22,591 26,973 143 627 495 881 7,086 9,517 3,374 159 2,307 3,763 a Sampaloc/S.Loyol 27 40,236 47,675 52 0 903 597 13,967 14,186 3,471 9,888 4,521 488 a Sta.Mesa/Altura 28 55,548 57,480 201 441 1,738 1,518 20,305 16,531 3,168 5,604 5,166 1,475 Ext. Old 29 51,717 57,580 201 925 2,479 2,985 17,771 17,757 4,829 942 4,390 6,300 Sta.Mesa/V.Mapa Sta.Mesa/P.Sanch 30 26,503 31,537 199 332 981 1,229 9,571 9,146 1,537 3,914 2,285 2,149 ez 31 Punta 42,315 41,852 156 334 1,336 1,103 12,671 10,651 3,916 3,003 4,512 1,243 Sta.Mesa/R.Mags 32 26,146 73,938 0 653 983 2,447 8,757 12,038 2,717 4,077 3,524 40,998 aysay San 33 6,790 21,795 930 392 96 119 2,234 4,622 576 959 547 12,524 Miguel/J.P.Laurel 34 Quiapo/C.Palanca 9,920 10,420 0 0 62 0 2,845 2,382 1,100 1,241 689 0 35 South Port Area 6,165 6,615 0 0 78 187 1,996 4,077 1,595 0 663 75 36 Intramuros/Muralla 6,081 45,061 54 1,213 121 1,605 2,567 16,476 839 327 165 22,175 Intramuros/Arrocer 37 3,104 73,442 0 957 76 2,385 1,199 29,037 220 955 272 37,344 os 38 Intramuros/Tanque 4,238 13,202 43 899 261 1,433 1,336 3,322 489 459 517 5,015 39 Ermita 4,472 40,119 0 419 0 2,406 1,720 33,310 551 125 491 1,242 40 Paco/Apacible 12,014 25,274 0 473 280 1,203 4,844 11,245 1,643 3,754 1,442 3,650 41 Paco/Canociga 24,742 29,530 213 231 1,235 730 7,035 5,561 2,075 3,852 2,267 3,759 42 Paco/Linao (Dart) 8,374 7,973 44 567 0 0 3,681 3,497 912 0 732 0 43 Malate/PCU 7,233 15,298 510 516 95 193 2,404 4,480 370 2,954 902 3,186 44 Malate/J.C.Bocobo 14,388 38,163 50 510 360 1,212 5,621 19,720 1,024 7,124 2,206 2,744 45 Malate/Harrison 18,043 26,821 0 453 827 2,006 6,837 13,225 2,222 173 1,404 2,181

B-15

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day Plaza San 46 40,940 38,823 119 710 2,557 1,146 14,185 11,928 2,625 641 4,646 2,328 Andres/L.Guinto 47 San Andres/SSH 17,452 16,217 71 23 936 781 7,387 6,332 714 0 1,525 210 San 48 27,826 23,671 166 44 2,178 551 9,204 8,322 3,006 357 2,032 33 Andres/Diamante 49 Paco/Fabie 20,295 25,698 51 43 750 555 4,784 5,314 1,583 4,284 2,015 930 50 Sta.Ana/Estrada 73,344 66,039 199 135 2,193 1,095 23,719 14,387 4,848 828 6,030 2,305 San 51 Miguel/Malacanan 10,210 14,754 0 123 390 1,037 2,397 4,536 671 267 1,446 1,887 g 52 Pandacan/Beata 50,771 49,799 731 599 1,960 892 18,768 13,440 2,627 3,663 3,632 1,115 Pandacan/T.Claudi 53 25,538 21,819 118 154 905 514 7,887 3,616 3,305 1,495 2,808 2,467 o Sta.Ana/Panadero 54 20,376 27,354 187 360 854 1,082 6,121 5,980 2,139 6,532 1,985 1,320 s Manila Noth 55 0 0 0000000 0 00 Harbour 56 MICT 0 0 0000000 0 00 57 BASECO 61,232 60,227 849 659 3,421 1,830 17,733 13,670 7,200 7,668 6,581 3,187 58 San Jose 27,544 33,877 506 1,285 409 997 4,458 5,915 2,621 5,083 2,806 431 59 San Isidro 21,984 21,447 124 302 512 608 6,519 4,022 2,420 2,249 1,872 1,123 60 Sta.Clara/Leveriza 22,704 26,794 156 375 304 676 4,430 7,133 3,127 1,303 2,439 2,400 61 Sta.Clara/Tramo 26,407 35,223 847 458 984 730 5,844 6,769 2,996 5,822 3,036 6,088 62 San Rafael 25,519 54,090 371 1,595 356 2,022 7,517 18,703 4,376 7,460 2,616 11,384 63 San Roque 49,114 50,276 226 78 867 1,187 12,576 10,539 6,451 6,891 3,553 1,156 64 Tabon 29,964 31,220 81 241 1,148 568 8,496 11,303 3,830 233 1,596 882 65 Malibay 79,112 87,978 1,135 1,427 2,676 1,905 21,660 18,581 11,574 15,911 6,059 6,786 66 Maricaban 61,153 57,554 409 589 1,781 1,082 14,919 12,725 8,641 6,881 5,429 338 67 Sto.Nino(Pasay) 30,216 24,635 465 181 623 628 7,921 5,035 3,008 447 2,983 106 68 Villamore Air Base 26,936 41,263 361 561 0 1,086 4,334 6,294 1,497 5,461 2,799 6,208 69 Air Cargo 25,024 31,676 1,436 755 907 501 6,120 4,832 3,057 8,014 2,338 3,824 70 Domestic Airport 4,677 5,923 353 88 72 164 1,322 2,401 347 105 429 568 PICC(reclamation 71 1,552 18,445 391 1,962 0 2,751 43 12,587 340 0 0 91 area) CITE(reclamation 72 2,218 29,274 123 1,569 104 3,860 680 22,970 833 143 0 33 area) 73 Bangkal 29,394 42,398 402 492 792 2,591 5,906 10,371 4,396 6,280 2,505 4,608 74 Palanan 26,994 42,259 1,230 364 632 2,149 4,652 16,534 2,419 3,391 3,208 2,435 75 Pio Del Pilar 41,962 64,861 499 1,361 466 3,366 12,106 24,717 6,286 8,347 3,914 4,765 76 Tejeros 36,977 36,695 425 232 1,303 1,549 8,982 7,327 4,677 6,253 1,983 316 77 Olympia 36,718 47,921 49 575 1,041 2,491 8,464 13,488 4,267 7,595 4,077 2,108 78 Poblacion(Makati) 25,830 50,080 403 1,344 649 4,869 8,825 21,137 3,410 3,226 2,092 6,992 79 Legaspi Village 5,146 23,766 0 1,510 0 2,460 1,645 15,629 0 0 447 537 80 San Lorenzo 3,346 42,886 0 1,982 0 5,104 772 30,196 0 0 553 2,312 81 Ayala Center 0 33,466 0 1,217 0 4,175 0 27,547 0 0 0 0 82 Salcedo Village 6,633 31,663 0 3,706 0 2,456 4,539 22,287 0 0 0 666 83 Bel-Air II 2,012 9,121 0 264 0 673 1,099 6,254 0 144 0 736 84 Urdaneta 2,653 34,755 0 1,169 0 3,890 400 26,786 69 0 0 122 85 Bel-Air I 5,835 26,733 216 1,600 0 1,794 3,172 20,241 0 0 0 0 86 Guadalupe Viejo 22,147 27,488 118 979 595 1,542 5,172 7,561 4,199 4,715 1,594 934 87 Guadalupe Nuevo 42,958 59,071 1,482 989 964 1,641 9,647 19,754 6,109 7,406 3,258 4,820 88 Cembo 50,456 44,276 446 115 771 650 13,678 7,521 4,841 6,887 6,222 978 Post Proper 89 8,455 4,652 763 111 0 0 1,906 575 1,518 464 1,218 0 Northside 90 Rembo 66,876 77,380 878 350 3,068 1,317 15,070 7,404 8,358 10,614 7,636 21,029 156,33 91 Pembo 173,048 2,232 1,420 2,916 2,032 39,655 20,947 24,118 23,971 15,661 7,188 4 101,62 92 Fort Bonifacio 30,371 1,190 3,740 979 14,970 3,903 57,393 4,379 3,305 2,500 4,259 1 93 Pinagsama 30,985 36,064 1,317 852 631 1,114 3,810 6,184 2,037 4,121 1,205 1,703 94 Dasmarinas/Forbs 5,886 11,902 0 1,020 0 1,424 1,872 4,973 364 871 614 0 95 Magallanes 4,673 17,769 0 289 0 1,769 1,855 12,701 395 0 836 1,068 96 Plainview 64,646 83,075 489 1,910 1,315 2,093 13,004 17,075 5,359 7,308 5,436 6,597 97 Old Zaniga 31,633 33,235 369 45 564 964 6,673 3,832 1,192 765 976 1,050 98 Poblacion(Mandal 40,683 50,351 102 448 1,478 880 11,308 14,710 5,040 6,180 4,567 5,674

B-16

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day uyong) 99 Hagdang Bato 35,980 56,200 547 324 563 1,766 8,237 9,043 3,089 7,200 2,876 13,326 100 Addition Hills 107,704 116,100 2,680 2,104 3,579 1,291 15,339 13,571 13,991 15,762 8,195 5,940 101 Barangka 36,934 60,055 552 1,207 1,550 3,724 9,033 20,246 3,105 2,133 3,935 10,130 102 Highway Hills 62,722 100,111 786 1,832 1,649 4,464 15,663 38,073 6,654 8,439 5,427 8,029 Wack- 103 10,697 69,636 0 4,496 0 10,606 0 52,247 0 0 0 828 Wack/Greenhills 104 Ortigas Center 0 18,217 0 918 0 3,188 0 13,992 0 0 0 0 105 East Greenhills 2,200 8,197 0 0 0 721 0 7,169 0 0 0 307 Greenhills Com'l 106 8,410 20,633 0 119 0 1,413 3,226 11,806 0 387 564 340 Center 107 West Crame 16,050 15,105 336 255 0 97 3,669 1,661 1,509 945 1,154 0 108 Batis 52,865 52,161 906 145 1,292 1,146 10,957 5,809 4,836 4,546 4,490 1,001 109 Corazon De Jesus 45,975 64,833 365 869 476 1,053 9,347 12,141 3,395 7,733 2,970 4,850 110 Dona Imelda 36,356 49,489 960 1,085 1,104 2,130 10,399 14,573 3,720 5,603 2,989 6,776 111 Santo Nino 35,759 41,513 239 119 1,253 641 9,875 11,048 2,485 5,464 2,167 2,867 112 Tatalon 79,790 72,525 1,286 1,308 2,705 1,689 15,501 11,565 9,535 7,415 6,235 2,113 113 Santa Teresita 25,752 35,424 419 404 790 1,703 7,082 14,436 2,240 2,620 532 137 N.S.Amoranto(Gint 114 31,085 32,164 822 1,167 992 1,027 6,789 6,336 3,005 1,496 2,508 3,413 ong Silahis) 115 Manresa 44,248 40,288 543 282 673 1,679 10,096 10,230 7,188 2,499 3,240 1,259 116 Balingasa 35,127 39,022 3,999 4,103 2,133 2,267 7,885 12,399 1,971 2,771 4,219 1,254 117 Apolonio Samson 47,784 60,339 828 1,179 1,491 2,289 8,528 18,096 3,353 4,300 2,443 507 118 Masambong 23,083 29,674 621 957 1,167 847 6,239 5,576 1,901 5,030 1,086 4,310 Santo 119 Domingo(Matalahi 17,177 21,668 270 1,008 694 1,473 5,091 9,747 2,119 77 591 615 b) 120 Del Monte 67,538 79,501 1,164 1,511 2,693 6,621 17,218 20,274 7,277 9,558 4,427 4,049 121 San Antonio 30,867 25,842 583 578 1,035 1,018 8,740 6,934 4,468 2,537 2,932 394 122 Veterans Village 27,894 39,625 1,226 1,331 571 2,276 5,349 11,122 5,052 7,648 2,342 2,559 123 Phil-Am 9,577 14,304 0 502 922 1,619 3,496 7,326 1,334 980 494 88 124 South Triangle 15,506 40,657 106 2,057 106 4,194 3,059 22,469 1,498 549 655 350 125 Kamuning 33,250 50,859 1,084 1,701 579 2,833 9,722 16,637 2,628 7,891 2,786 4,168 126 Roxas 38,826 45,472 1,282 1,375 779 1,122 10,791 13,702 4,420 3,896 2,478 4,163 127 Kalusugan 24,881 24,322 608 315 723 619 6,973 9,267 3,907 680 1,925 1,756 128 Mariana 19,397 22,674 134 586 1,325 1,513 2,199 4,945 1,865 548 568 354 129 Kaunlaran 25,552 31,489 1,415 560 666 1,591 5,218 8,433 1,977 3,695 3,046 3,093 Immaculate 130 19,477 21,466 181 367 226 865 5,355 2,940 1,065 875 2,037 4,966 Concepcion Bagong Lipunan 131 26,316 28,864 643 625 594 1,360 6,103 10,377 2,956 1,334 3,144 1,206 Crame 132 Crame 5,970 2,228 0 0 0 0 0 1,724 0 322 0 302 133 Ugong Norte 13,282 3,322 0 151 0 389 0 1,953 0 0 0 749 134 Camp Aguinaldo 6,609 14,799 0 0 0 633 1,651 6,426 544 653 414 2,646 135 White Plains 18,493 29,567 0 1,478 768 3,413 5,683 13,444 3,162 2,910 1,735 551 136 Murphy District 25,701 94,419 112 3,338 2,293 12,029 7,511 57,887 3,741 1,325 1,294 6,611 Cubao(Araneta 137 0 8,725 0 660 0 3,554 0 4,510 0 0 0 0 Center) 138 E. Rodriguez 30,134 50,346 793 1,018 459 2,447 7,809 16,251 2,688 5,461 2,186 7,601 139 San Roque 72,767 95,369 1,453 1,127 1,272 3,205 17,065 14,725 7,156 13,975 5,738 18,144 140 Escopa 27,960 42,131 74 2,678 801 3,592 7,039 19,056 2,103 372 3,419 620 141 Quirino 3 17,683 22,370 111 276 483 523 5,111 5,058 1,770 2,859 1,047 3,930 142 Quirino 2 30,717 39,101 582 1,424 518 1,571 7,951 8,904 2,114 5,544 3,024 3,407 143 Loyola Heights 72,169 68,604 529 786 1,953 1,810 19,056 15,015 7,857 7,376 6,472 4,572 144 Teachers Village 24,156 23,917 937 770 0 1,344 7,890 8,792 1,897 572 2,296 486 126,42 145 QMC 79,950 2,054 5,883 1,592 4,753 22,918 60,374 4,738 5,788 7,606 5,573 3 146 U.P. Campus 73,992 79,960 1,937 2,186 1,495 1,676 23,249 26,071 5,532 3,016 6,048 7,723 185,10 147 Batasan Hills 191,323 6,290 3,818 7,676 5,323 47,995 34,226 21,768 26,342 17,620 17,366 3 148 Matandang Balara 90,474 79,455 3,671 1,469 4,247 3,148 22,325 17,173 9,110 6,217 6,559 3,952 149 Holy Spirit 123,011 114,703 3,741 3,047 7,316 2,720 28,050 18,354 11,901 17,133 9,322 6,789 122,16 150 Payatas 151,437 4,306 2,042 6,178 2,626 38,067 17,471 19,556 19,967 14,532 5,400 4 151 Bagong Silangan 0 0 0 0 0 0 0 0 0 0 0 0 152 Constitution Hills 102,828 85,417 1,078 107 5,623 2,303 26,549 11,956 10,665 10,678 10,027 7,572

B-17

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 280,63 153 Commonwealth 255,435 6,919 6,491 7,554 8,730 64,215 63,663 30,580 36,845 21,435 28,159 4 154 Fairview 60,623 73,079 1,830 1,505 2,631 2,926 15,733 20,611 6,944 7,556 5,284 10,948 193,73 155 Pasong Putik 119,842 3,138 6,137 5,931 7,666 24,225 57,003 12,824 17,068 13,113 37,626 8 156 Kaligayahan 121,127 119,027 3,431 1,951 5,800 3,851 24,744 20,724 16,540 15,763 14,684 16,282 162,47 157 San Agustin 119,650 2,361 3,079 5,239 12,147 26,699 48,828 16,032 16,634 9,391 15,927 3 162,75 158 Gulod 151,957 4,786 3,331 5,722 4,174 31,620 27,891 16,852 20,755 14,841 22,218 5 159 Sauyo 101,267 84,310 1,466 361 2,917 2,825 24,537 9,450 9,721 8,955 9,825 5,135 160 Bagbag 52,567 47,353 574 259 3,475 2,666 10,857 8,257 6,464 6,652 5,155 1,490 172,70 161 Tandang Sora 161,782 4,578 3,242 5,709 5,072 34,123 38,459 16,273 19,248 14,169 12,415 4 111,47 162 Pasong Tamo 89,157 2,418 1,080 4,060 1,386 29,293 17,592 12,902 11,262 8,474 654 6 163 Culiat 86,719 80,462 1,623 710 3,896 1,004 19,358 14,524 11,307 10,781 7,521 6,561 145,72 164 Project 6 84,607 1,153 4,914 1,411 6,390 20,204 64,953 8,308 8,341 6,220 8,656 9 Ramon 165 41,350 58,297 684 1,438 830 2,118 8,502 14,551 2,881 4,230 4,844 9,665 Magsaysay 166 Bahay Toro 95,165 96,558 2,032 1,580 4,710 5,672 28,044 28,263 10,029 9,331 5,644 3,840 167 Baesa 87,976 77,855 607 1,271 4,406 4,284 20,388 13,085 10,727 10,388 7,796 2,349 168 Sangandaan 30,564 36,590 1,145 885 1,333 1,078 5,324 5,943 3,188 5,184 3,557 5,298 169 Bo. San Jose 31,181 25,784 1,262 609 636 315 9,874 7,598 4,244 3,256 3,058 208 170 West 3/4 Ave. 39,332 36,330 839 546 902 1,499 7,738 6,484 4,524 3,224 4,306 1,209 142,44 171 A.Mabini 162,164 1,833 723 3,905 1,924 37,451 21,084 21,453 18,622 12,403 4,244 2 132,41 172 Dagat Dagatan 137,380 3,206 2,027 4,608 3,971 29,250 23,115 18,265 19,730 12,843 5,342 0 105,57 173 West 8/10 Ave. 75,942 1,510 2,941 1,681 3,214 17,719 29,425 9,224 11,400 9,301 16,843 7 174 Grace Park 58,977 79,712 734 1,572 1,179 3,328 14,632 22,115 8,207 9,574 5,585 10,636 175 Sangandaan 22,231 45,500 0 783 149 1,955 4,182 10,484 1,369 1,317 1,106 13,672 Bagon Barrio 176 21,554 38,557 329 1,670 329 2,075 8,020 12,997 1,689 4,748 870 5,388 EDSA Bagon Barrio 177 91,267 79,053 1,665 262 5,022 2,108 18,744 11,006 11,580 9,373 8,453 4,438 Center 178 Bagon Barrio East 94,234 91,283 1,896 1,070 3,321 2,552 18,390 13,036 12,909 14,669 8,801 6,090 146,18 179 Bagumbong 1(CN) 148,089 1,336 1,143 7,966 4,659 28,439 20,567 21,240 20,565 14,733 15,158 2 180 Bagumbong 2(CN) 101,994 111,852 1,594 956 3,982 4,928 20,298 20,360 12,140 16,294 8,726 6,523 181 Bagumbong 3(CN) 55,321 56,890 1,626 866 2,613 2,019 9,847 6,241 9,375 12,441 5,921 5,955 182 Camarin 1(CN) 108,378 116,705 1,241 1,100 5,663 4,224 30,356 23,786 13,023 16,416 13,168 20,232 221,97 183 Camarin 2(CN) 223,803 1,685 1,349 7,816 1,918 41,067 28,766 26,613 30,728 16,040 11,628 0 301,67 184 North 1(CN) 309,400 2,628 1,907 13,522 5,417 57,670 35,509 41,539 47,439 27,890 23,408 3 189,58 185 West(CN) 203,542 4,755 3,472 10,583 3,521 44,143 25,808 25,078 25,951 20,338 19,251 1 186 Canumay 110,162 118,192 1,274 1,320 6,839 8,968 24,773 22,436 16,439 16,632 9,307 9,379 Mapulang 187 91,370 96,371 4,354 4,655 4,718 5,296 14,263 10,428 11,484 11,875 9,540 9,777 Lupa/Ugong 188 Bagbaguin 31,814 44,864 788 1,020 1,582 3,616 6,974 14,501 3,271 5,296 2,420 1,078 189 Hen. T. De Leon 99,969 98,071 3,513 1,946 3,534 1,259 17,998 10,101 13,485 14,755 7,461 7,492 190 Marulas 59,365 80,510 110 255 576 1,931 6,883 8,132 3,993 6,362 3,003 12,010 147,51 191 Karuhatan 101,176 1,324 2,170 1,857 6,893 15,140 35,385 6,331 9,826 7,089 12,741 0 192 Maysan 76,361 69,913 1,510 1,291 5,515 4,147 16,147 11,681 6,955 7,728 9,700 3,053 193 Malanday(Val.) 55,575 60,117 950 1,562 1,012 1,248 9,118 9,101 5,433 5,788 3,283 1,396 194 Dalandanan 62,707 81,571 248 777 3,997 5,512 12,308 15,387 10,386 12,684 5,461 12,271 195 Maysilo/Panghulo 46,005 48,448 609 322 2,564 1,316 9,631 7,024 5,133 6,584 3,897 2,446 196 Potrero 41,339 51,576 842 705 1,948 3,999 4,050 4,775 5,992 7,915 3,429 2,077 197 Tugatog 49,182 65,329 419 374 1,451 3,301 14,962 14,333 5,455 10,687 3,603 6,816 198 Longos 63,169 86,394 1,094 2,232 1,465 1,250 10,890 12,565 6,344 9,755 3,640 9,270 199 Tonsuya 86,164 93,422 1,756 799 2,252 1,429 15,752 15,436 8,879 8,575 5,690 1,069 Baritan/Concepcio 200 66,244 88,632 1,489 2,312 1,263 1,158 12,973 16,290 7,546 12,974 7,947 10,623 n

B-18

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 201 Dampalit 17,399 16,683 557 421 1,575 1,599 3,810 2,689 2,443 1,625 609 0 202 Tanza 27,731 26,104 1,087 451 1,068 208 6,651 4,312 4,495 4,183 2,494 1,727 203 Tangos 54,194 61,433 3,643 2,724 1,152 943 7,593 6,876 6,293 7,636 2,718 1,438 204 San Jose 64,201 87,589 556 1,170 919 1,648 7,767 11,185 3,901 7,610 2,532 4,443 205 Navotas East/West 45,874 53,775 875 795 1,120 1,769 4,074 4,378 4,627 3,751 1,476 107 206 North Bay Blvd. 78,499 96,065 2,123 4,714 2,677 3,397 11,934 12,721 8,196 9,791 7,464 6,885 207 Navotas Fishport 0 0 0 0 0 0 0 0 0 0 0 0 208 Nangka 43,438 45,037 541 837 2,531 1,532 12,767 9,694 6,319 7,954 3,455 3,132 103,17 209 Parang 78,342 433 405 2,997 5,192 7,099 9,724 2,837 6,162 3,807 4,765 2 Concepcion(Mariki 210 89,198 109,844 1,306 952 4,334 2,894 19,196 21,442 8,816 11,355 8,814 14,554 na) 211 Marikina Heights 63,771 73,453 665 665 1,916 1,629 13,290 14,213 5,151 5,116 5,450 4,768 Calumpang/San 212 42,614 91,784 721 947 1,242 5,283 10,069 33,674 3,525 8,973 5,441 15,367 Roque 213 Santo Nino 29,667 43,246 724 794 1,256 3,556 8,896 15,078 3,303 4,493 2,283 2,491 214 Malanday(Marikina) 57,043 62,666 702 884 2,408 793 10,352 8,153 3,469 4,168 2,978 2,052 215 Barangka(Marikina) 57,929 70,145 389 226 1,310 1,908 12,111 14,479 4,536 6,323 4,444 3,096 216 Kalawaan 69,744 68,701 1,067 603 2,108 2,519 9,398 7,756 6,522 8,362 5,182 3,691 Santolan/Manggah 217 226,813 248,148 4,962 4,595 8,147 17,807 45,738 59,681 26,067 23,988 19,045 17,210 an 218 Santa Lucia 57,842 59,635 735 237 1,177 1,535 9,740 7,675 5,702 8,007 4,367 5,592 219 Maybunga 45,061 53,359 409 987 2,297 3,804 7,026 7,421 2,320 5,154 3,357 5,971 220 Ugong 28,211 45,481 1,574 1,736 660 4,221 4,418 19,850 3,211 3,629 3,235 609 221 San Antonio 27,646 73,007 108 2,472 108 6,057 3,334 39,043 1,218 1,580 1,030 1,097 222 Kapitolyo 45,083 46,130 862 1,296 1,857 2,109 12,359 13,434 4,224 3,731 4,821 4,437 223 Bagong Ilog 22,561 21,593 82 499 905 1,441 4,161 4,655 2,732 1,941 1,873 88 122,66 224 Bambang 96,267 1,800 1,951 2,894 5,235 14,083 27,945 6,753 11,999 5,304 9,056 9 225 Caniogan 86,957 94,365 1,556 2,052 2,126 2,357 17,700 13,118 7,845 10,340 6,509 14,365 226 Pinagbuhatan 195,314 169,768 2,668 2,210 6,212 3,196 32,468 19,138 19,139 15,701 14,725 8,304 Santa 227 72,500 86,590 3,267 2,880 2,333 1,213 18,899 20,067 7,290 9,860 7,461 10,804 Ana(Pateros) 228 Bagumbayan 119,234 112,003 1,376 1,227 5,870 5,302 22,138 15,714 16,534 18,960 8,486 5,274 229 Bicutan 223,873 215,401 3,674 3,148 9,070 7,828 48,247 38,241 30,632 26,715 24,758 30,371 230 Signal Village 99,052 99,223 457 291 1,040 442 12,903 10,137 5,525 8,320 5,553 5,993 231 Western Bicutan 95,695 95,463 1,355 1,015 5,209 3,562 12,248 14,223 13,254 13,745 9,250 7,961 232 Hagonoy 123,601 105,133 1,225 1,068 2,197 1,173 16,469 7,035 9,524 7,370 8,026 1,325 233 Ususan 183,189 168,311 4,723 3,650 10,939 7,268 40,004 31,395 25,194 25,132 18,976 16,765 234 Baclaran 23,029 52,551 452 560 705 2,479 7,215 26,749 2,718 6,785 3,087 6,156 235 Tambo 33,856 43,521 233 1,013 1,208 3,156 5,537 12,632 5,227 4,880 2,066 667 236 La Huerta 12,753 22,050 241 107 0 127 3,116 6,102 2,306 4,573 1,114 4,685 237 San Dionisio 77,567 97,440 1,403 2,718 1,094 2,446 22,779 24,831 9,506 13,838 9,796 17,205 238 Moonwalk 86,279 81,335 1,794 1,258 4,913 3,583 20,437 13,398 11,459 11,866 7,821 8,347 Santo Nino 239 42,176 48,105 869 1,119 1,753 1,475 10,924 16,143 5,675 5,183 2,449 1,778 (Paranaque) 240 Merville 29,348 22,186 1,643 957 1,906 1,645 4,842 4,540 4,233 179 2,708 0 241 Sun Valley 73,682 77,137 1,371 1,135 2,634 3,084 20,132 19,694 9,410 8,756 6,392 8,015 242 Don Bosco 65,619 81,406 627 1,685 3,296 4,538 15,573 25,002 12,386 16,881 5,564 2,573 Marcelo Green 243 36,914 28,780 0 139 2,245 1,621 8,153 6,367 4,888 115 1,808 0 Village 244 San Antonio 79,629 92,864 2,148 611 2,204 2,932 9,420 16,021 8,264 13,180 5,313 3,651 245 San Isidro 96,284 80,868 1,783 398 2,419 1,900 21,084 17,023 17,983 9,722 8,851 4,079 246 B.F.Homes 33,633 31,413 167 335 1,695 1,244 6,212 4,700 2,852 1,541 1,423 755 247 B.F.Homes 62,167 64,915 1,783 1,617 523 2,687 16,768 17,212 6,973 6,929 3,577 1,191 248 B.F.Homes 12,499 12,982 284 208 143 164 2,483 3,226 1,564 1,351 740 162 249 NAIA 2,876 5,507 0 0 0 0 719 890 529 2,459 161 387 Marina Manila 250 15,562 15,868 244 381 631 869 2,565 1,002 2,875 2,975 1,198 2,221 Baytown 251 Sucat 63,351 77,481 502 1,203 2,685 4,205 10,240 13,360 5,031 5,669 6,597 9,336 252 Cupang 67,248 62,171 819 955 1,987 3,817 12,216 5,746 8,340 5,819 4,540 1,160 253 Alabang 114,440 203,516 1,842 4,490 4,370 12,759 21,198 74,454 12,257 21,298 7,412 13,208 254 New Alabang Village 26,058 19,273 2,966 730 448 357 7,489 3,878 1,908 633 1,195 136 255 Putatan 99,037 100,133 2,203 1,323 4,130 3,534 20,335 18,181 13,122 15,645 8,573 4,880 256 Pob. (Muntinlupa) 132,831 143,081 1,807 2,199 3,753 1,740 30,440 21,642 14,573 16,382 13,239 23,437

B-19

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 257 Tunasan 61,035 73,130 1,680 1,960 3,350 4,514 11,850 19,570 9,012 8,995 4,289 3,256 258 Manuyo 62,126 65,521 228 420 2,764 2,033 15,590 12,980 8,455 8,164 5,229 6,739 Elias 259 Aldana/Daniel 31,222 32,050 317 633 1,473 628 7,862 4,914 3,970 5,311 2,206 2,614 Fajardo 260 Pulang Lupa 68,697 72,939 700 1,631 3,123 4,897 18,598 17,948 9,338 8,620 5,522 2,378 261 Pamplona 106,793 138,454 2,932 2,716 4,989 7,483 22,439 23,508 11,798 19,465 7,221 16,641 262 B.F.International 110,611 120,979 2,079 1,176 4,755 4,905 26,444 19,363 15,463 20,809 7,827 10,142 263 Talon 111,837 128,400 1,792 2,274 5,957 5,227 21,986 22,159 17,269 21,560 8,243 9,394 264 Pilar 80,033 82,475 1,149 816 4,227 2,850 17,668 15,105 13,343 14,191 5,181 4,130 265 Almanza 80,681 104,443 1,550 2,354 2,743 2,969 9,222 17,696 8,850 12,559 5,954 6,642 266 Obando 68,000 74,336 2,144 2,261 2,822 2,157 15,406 16,432 10,826 12,485 5,016 3,020 267 Marilao(West) 150,178 93,114 1,261 1,589 8,780 6,121 36,358 24,195 32,549 18,112 13,745 10,591 Meycauayan(West 165,09 268 170,092 1,905 1,558 9,175 8,394 42,042 38,089 30,210 30,907 13,272 13,316 ) 1 245,18 269 SJDM(West) 341,273 10,042 9,078 14,778 14,203 93,690 47,319 32,044 24,668 29,245 26,335 2 270 Norzagaray 167,500 130,311 7,701 6,831 9,801 6,713 25,236 16,346 30,707 26,609 16,247 9,402 124,61 271 Santa Maria(West) 144,365 2,085 2,081 10,798 9,873 40,128 38,763 23,369 19,473 11,030 13,084 8 146,94 272 Bocaue 149,000 4,104 4,710 9,411 9,732 31,414 31,047 31,786 31,584 14,310 13,186 4 273 Bulacan 90,500 90,792 5,073 5,747 5,858 4,752 23,502 23,093 12,125 12,779 7,127 4,702 100,14 274 Balagtas 82,000 2,343 2,199 4,425 5,831 18,470 27,496 14,008 14,846 6,221 8,691 7 275 Pandi 114,500 92,754 5,273 4,166 4,465 2,213 24,706 17,574 15,578 13,634 7,358 6,356 125,81 276 Guiguinto 147,000 2,270 2,057 9,195 8,550 42,723 37,444 18,832 16,332 14,655 10,007 6 133,36 277 Plaridel 149,000 1,901 1,936 4,465 3,233 42,488 37,998 31,881 29,924 12,908 8,276 8 278 Pulilan 125,500 110,433 3,395 3,188 10,882 8,497 33,976 28,095 7,669 7,606 11,439 7,891 185,12 279 Malolos(North) 180,806 5,994 5,822 4,806 5,536 42,277 38,521 28,919 23,295 19,208 42,834 5 280 Paombong 72,000 59,880 5,529 5,172 2,927 1,049 15,604 11,169 11,638 11,111 6,769 3,832 154,47 281 Hagonoy 153,000 6,639 6,235 3,684 2,112 34,174 29,525 26,406 29,590 12,582 10,048 8 132,93 282 Calumpit 145,500 2,171 1,825 5,845 5,637 37,502 34,191 17,663 16,476 9,620 4,069 5 169,71 283 Gen. Mariano Alvarez 183,500 2,916 2,389 12,405 6,964 56,527 45,910 21,465 21,477 11,690 11,448 2 164,79 284 Dasmarinas(West) 163,088 4,518 4,832 15,360 10,187 55,114 59,623 17,426 22,926 8,377 16,698 1 285 Bacoor(North) 136,455 96,637 3,060 1,303 5,226 5,282 36,197 24,544 17,589 13,256 7,986 1,510 168,00 286 Imus(North) 166,777 1,948 1,495 15,640 16,735 50,588 54,346 9,720 12,864 6,074 9,598 0 287 Kawit 105,000 100,211 2,443 1,981 8,905 6,170 28,095 26,617 15,638 14,881 8,288 7,586 123,40 288 Cavite City 103,500 2,352 1,955 5,622 3,618 36,352 41,412 5,402 7,529 7,598 9,148 8 289 Noveleta 59,500 52,507 665 473 2,611 681 16,999 14,557 7,556 5,919 5,124 4,408 199,09 290 Rosario 124,000 6,022 8,961 14,133 48,254 39,898 70,026 7,889 9,185 4,788 9,642 4 General 121,79 291 262,945 9,462 3,953 34,511 13,163 86,007 36,400 18,481 8,879 7,752 4,585 Trias(North) 5 129,94 292 Tanza(North) 194,907 8,610 5,698 15,904 3,802 65,673 42,467 7,985 8,140 6,905 4,608 7 147,71 293 Trece Martires 343,500 4,050 2,849 36,227 14,192 99,606 36,613 43,562 20,396 23,084 10,686 9 294 Naic 114,000 113,765 7,464 7,043 5,234 2,520 26,907 25,714 19,632 20,929 7,003 6,571 295 Silang(West) 135,530 127,115 4,047 3,112 12,524 9,645 34,839 30,575 25,523 25,543 7,828 9,783 296 Carmona 135,000 119,726 3,634 3,920 13,264 12,836 35,888 36,419 17,657 14,225 9,119 7,255 196,12 297 San Pedro(North) 191,301 1,570 1,204 9,470 7,629 48,824 38,019 26,471 29,050 17,216 20,157 2 266,27 298 Binan(North) 238,233 9,032 9,134 10,119 7,873 51,103 59,811 35,002 43,342 22,485 27,344 4 331,97 299 Santa Rosa(Center) 334,392 8,932 8,901 22,778 18,396 75,334 79,691 44,643 42,525 25,077 26,486 3 153,45 300 Cabuyao(North) 215,971 5,771 3,755 13,243 9,417 48,703 29,625 31,295 23,695 16,832 11,087 0

B-20

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day City of 253,54 301 239,397 9,875 9,744 9,762 7,015 42,873 43,221 37,438 40,715 15,735 18,218 Calamba(Center) 3 140,89 302 Los Banos 123,000 3,988 4,264 3,540 2,839 27,455 29,754 17,368 20,125 9,735 13,394 4 258,66 303 Taytay(West) 306,228 2,671 1,431 16,442 13,332 70,755 46,767 32,055 29,491 40,815 30,732 0 220,79 304 Cainta(South) 250,113 2,944 892 12,541 7,795 52,714 34,706 32,467 26,946 23,540 14,573 0 364,48 305 Antipolo(Center) 394,810 11,967 10,450 25,899 22,181 82,464 61,872 51,050 54,108 36,516 36,532 9 172,53 306 San Mateo(South) 207,766 2,563 1,379 10,769 7,250 42,774 29,606 22,058 19,491 14,165 7,914 4 212,51 307 Rodriguez(West) 381,084 2,425 1,601 21,626 7,939 83,805 36,298 46,086 30,935 36,570 20,405 4 132,06 308 Angono 146,500 2,643 2,295 9,300 6,074 34,996 26,469 15,580 15,279 21,405 19,461 2 286,16 309 Binangonan(North) 309,319 23,697 23,890 16,357 12,540 69,189 52,047 40,297 40,967 24,881 19,820 0 310 Cardona 59,000 58,418 3,507 2,948 3,245 2,429 11,684 9,529 6,033 6,544 6,013 4,532 311 Morong 65,500 76,514 3,142 1,820 3,290 3,085 15,064 14,343 12,693 14,391 6,120 14,809 312 Teresa 78,000 60,600 2,070 2,179 4,105 3,608 22,114 16,288 8,724 7,684 8,032 2,210 313 Baras 45,500 40,743 820 940 3,264 2,085 13,290 11,220 4,020 4,041 5,414 3,669 138,17 314 Tanay 128,500 6,290 6,401 8,497 8,617 24,056 25,644 19,712 21,645 13,687 14,471 9 315 Pililia 81,000 77,936 5,971 5,936 3,564 2,997 12,678 9,466 11,741 11,949 8,668 8,844 316 Jalajala 40,000 39,273 2,946 3,126 1,523 984 8,599 7,938 6,334 6,740 3,890 2,863 317 North 2(CN) 23,211 20,485 0 664 1,442 560 5,373 3,061 2,529 3,226 2,727 518 Manila Harbour 318 0 0 0000000 0 00 Center 319 Manila South Harbour 0 0 0 0 0 0 0 0 0 0 0 0 320 NAIA Terminal 1 0 6,052 0 498 0 666 0 4,887 0 0 0 0 321 NAIA Terminal 2 0 2,239 0 487 0 0 0 1,752 0 0 0 0 322 NAIA Terminal 3 0 3,300 0 0 0 371 0 2,930 0 0 0 0 NAIA Domestic 323 0 1,331 0 0 0 0 0 1,331 0 0 0 0 Terminal 178,22 324 Marilao(East) 355,822 3,795 1,419 34,833 14,411 61,526 26,763 69,049 37,276 35,496 14,386 1 103,58 325 Meycauayan(East) 107,908 1,426 1,699 9,692 13,058 23,150 22,226 23,609 22,141 9,405 4,724 3 326 SJDM(East) 165,685 116,319 2,359 2,195 10,389 5,732 37,352 23,852 23,796 18,099 16,346 9,585 208,14 327 SJDM(North) 327,542 13,103 6,085 23,470 6,877 67,870 34,026 52,536 38,271 29,937 16,161 6 189,93 328 Santa Maria(West) 290,135 5,164 3,005 12,192 7,185 75,724 45,897 51,517 34,678 25,186 12,549 6 181,05 329 Malolos(South) 203,194 8,678 8,178 9,078 6,601 56,609 52,325 31,051 29,634 19,640 16,526 0 277,74 132,35 330 Dasmarinas(Center) 409,834 3,672 267 33,122 16,584 76,925 38,971 23,851 19,185 12,320 5 8 142,96 331 Dasmarinas(East) 225,612 3,167 1,583 27,249 9,758 52,766 21,007 21,394 15,770 15,504 9,688 0 Dasmarinas(South 212,21 332 196,465 4,183 5,455 23,179 40,695 64,759 78,005 20,291 18,572 11,011 9,597 ) 7 233,79 333 Bacoor (Coastal) 331,596 7,250 5,670 27,158 12,188 79,352 53,933 53,429 38,598 22,736 13,120 3 198,41 334 Bacoor(Center) 282,799 4,936 1,721 22,395 15,009 69,128 39,091 40,700 31,481 20,261 14,222 7 206,37 335 Bacoor(South) 292,149 3,627 985 23,863 16,613 69,149 42,609 43,574 32,796 18,685 11,273 2 196,55 336 Imus(Center) 211,920 3,433 2,780 16,238 20,188 55,270 59,929 19,049 14,740 17,390 9,644 2 337 Imus(South) 154,303 118,478 5,515 3,863 10,919 8,676 41,263 20,723 15,930 13,032 9,032 8,927 General 221,95 338 438,555 11,313 8,235 58,461 24,097 113,884 58,979 38,911 20,167 28,349 13,930 Trias(South) 4 339 Tanza(South) 186,093 112,450 9,511 5,288 18,526 5,909 38,636 18,310 22,004 13,730 8,974 5,315 155,44 340 Silang(Eest) 186,470 7,673 7,041 13,296 10,829 57,823 40,730 20,301 18,878 14,871 9,456 0 195,73 341 San Pedro(South) 172,699 3,631 4,244 9,362 11,783 45,825 49,036 25,051 29,710 11,945 12,922 9 342 Binan(South) 144,767 159,54 1,913 2,393 9,107 20,397 41,201 45,297 19,420 16,589 14,785 12,280

B-21

Student Population Primary Secondary Tertiary Student(Elem.) Zone NAME (H.S.&Univ.) Night Day Night Day Night Day Night Day Night Day Night Day 5 343 Santa Rosa(West) 80,608 84,420 2,075 2,508 4,654 10,534 18,420 21,118 13,470 13,149 6,758 3,174 228,81 344 Cabuyao(South) 304,529 7,764 7,502 20,306 14,856 58,485 42,602 44,466 32,626 25,564 19,469 7 225,92 345 City of Calamba(West) 209,679 3,857 4,001 14,781 16,560 36,101 37,953 29,225 31,616 12,328 12,891 8 346 City of Calamba(East) 67,923 85,007 808 1,495 2,683 6,254 11,099 17,508 8,501 9,936 3,055 3,553 135,87 347 Taytay(East) 135,272 1,789 1,340 12,069 9,583 30,515 35,503 17,323 19,081 12,290 9,798 0 201,52 348 Cainta(North) 162,887 1,963 3,761 7,120 10,048 37,030 45,707 20,805 19,599 19,046 38,191 9 235,00 349 Antipolo(South) 254,610 2,981 4,272 13,953 11,461 50,655 42,979 32,510 34,385 26,492 19,841 6 195,93 350 Antipolo(North) 257,471 1,854 1,235 15,988 8,067 52,962 30,617 32,684 21,737 25,562 13,077 7 351 Antipolo(North-East) 113,109 94,977 1,235 1,142 6,513 4,190 15,903 9,761 14,277 12,338 10,076 6,137 352 San Mateo(North) 118,734 96,602 2,893 1,218 5,916 2,626 23,667 15,486 13,502 12,228 8,244 4,847 198,37 353 Rodriguez(East) 374,916 4,294 2,132 22,812 9,703 65,421 25,039 58,027 31,874 32,137 14,519 7 354 Binangonan(South) 35,681 32,410 6,499 5,348 1,603 975 5,181 3,975 2,903 2,529 3,095 2,345 29,726,99 Total 29,726,999 640,227 632,486 1,562,707 1,455,896 7,006,614 7,009,657 3,652,663 3,615,920 2,465,695 2,497,853 9

B-22

APPENDIX C: ESTIMATED CAR OWNERSHIP Table C-1: Car Ownership Household Rate

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 1 17,773 15.0 26.8 43.5 2 17,171 10.1 21.5 37.6 3 17,329 17.2 28.7 45.0 4 17,542 11.4 23.1 39.5 5 17,597 16.5 28.2 44.7 6 24,238 17.0 33.1 55.8 7 21,886 8.6 23.2 43.7 8 25,558 30.9 47.9 71.9 9 20,672 23.8 37.5 56.9 10 20,302 22.3 35.8 54.8 11 34,975 45.2 68.4 100.0 12 20,534 37.1 50.7 70.0 13 24,615 23.1 39.4 62.5 14 23,507 30.6 46.2 68.2 15 13,663 5.9 14.9 27.8 16 22,538 19.6 34.6 55.7 17 22,981 15.9 31.2 52.8 18 30,646 35.5 55.9 84.6 19 16,694 8.2 19.3 35.0 20 16,038 13.3 24.0 39.0 21 24,866 26.8 43.4 66.7 22 29,576 23.7 43.4 71.2 23 31,789 37.7 58.8 88.7 24 28,745 34.3 53.4 80.3 25 28,424 29.4 48.3 75.0 26 19,988 27.6 40.9 59.6 27 19,889 23.2 36.4 55.1 28 20,880 25.6 39.5 59.1 29 26,574 25.1 42.8 67.7 30 23,632 39.8 55.5 77.6 31 24,333 25.6 41.8 64.6 32 27,830 26.8 45.3 71.4 33 21,971 20.2 34.8 55.5 34 13,182 0.0 8.8 21.1 35 12,500 0.0 8.3 20.0 36 15,591 22.3 32.7 47.3 37 18,253 35.5 47.6 64.7 38 18,229 14.2 26.3 43.4 39 20,061 26.8 40.2 59.0 40 16,675 16.3 27.3 43.0 41 16,507 25.6 36.6 52.1 42 18,974 32.8 45.4 63.3 43 14,200 9.3 18.8 32.1 44 23,504 23.7 39.4 61.4 45 12,699 4.7 13.1 25.1 46 25,221 18.7 35.4 59.1 47 33,111 48.5 70.5 100.0 48 16,161 19.6 30.4 45.6 49 22,089 34.1 48.8 69.5 50 23,051 14.8 30.1 51.8 51 17,159 10.2 21.6 37.7 52 17,316 17.3 28.8 45.1 53 31,277 17.8 38.6 67.9 54 26,728 29.8 47.6 72.6 55 0 0.0 0.0 0.0 56 0 0.0 0.0 0.0 57 14,182 12.5 22.0 35.3 58 16,641 10.7 21.7 37.3 59 25,734 27.8 44.9 69.1 60 17,472 4.6 16.2 32.6 61 23,027 10.8 26.1 47.7 62 16,314 15.3 26.2 41.5 63 16,091 6.5 17.2 32.3 64 15,810 3.6 14.1 28.9 65 18,183 8.8 20.9 38.0

C-1

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 66 19,275 6.7 19.5 37.6 67 23,414 23.3 38.9 60.9 68 17,124 32.8 44.2 60.3 69 15,253 5.5 15.6 29.9 70 20,112 42.3 55.7 74.6 71 8,750 0.0 5.8 14.0 72 7,500 0.0 5.0 12.0 73 22,067 26.0 40.6 61.4 74 26,497 12.5 30.2 55.0 75 20,958 28.6 42.5 62.2 76 20,806 13.6 27.4 46.9 77 25,000 21.3 37.9 61.4 78 16,176 16.8 27.6 42.7 79 30,378 76.7 96.9 100.0 80 42,021 88.5 100.0 100.0 81 0 0.0 0.0 0.0 82 79,839 90.8 100.0 100.0 83 287,500 100.0 100.0 100.0 84 37,732 76.7 100.0 100.0 85 348,571 100.0 100.0 100.0 86 15,938 0.0 10.6 25.6 87 27,326 25.1 43.2 68.9 88 22,077 13.4 28.1 48.8 89 14,032 19.1 28.4 41.6 90 17,684 7.9 19.7 36.3 91 19,951 21.1 34.3 53.1 92 17,711 11.9 23.6 40.3 93 16,262 6.2 17.0 32.3 94 123,177 97.3 100.0 100.0 95 27,551 66.4 84.8 100.0 96 26,150 25.1 42.5 67.0 97 22,811 4.6 19.7 41.1 98 16,658 16.3 27.3 43.0 99 19,106 14.5 27.2 45.1 100 15,471 5.4 15.7 30.2 101 20,023 24.6 37.9 56.7 102 27,776 20.9 39.3 65.4 103 0 0.0 0.0 0.0 104 0 0.0 0.0 0.0 105 0 0.0 0.0 0.0 106 20,833 0.0 13.8 33.4 107 18,941 16.3 28.8 46.6 108 21,700 14.3 28.7 49.0 109 19,956 13.7 27.0 45.7 110 14,455 4.8 14.4 28.0 111 16,399 9.3 20.2 35.6 112 17,441 6.6 18.2 34.6 113 17,491 11.9 23.5 39.9 114 14,798 0.0 9.8 23.7 115 20,460 13.2 26.8 46.0 116 23,228 35.9 51.3 73.1 117 14,425 0.0 9.6 23.1 118 12,738 0.0 8.5 20.4 119 21,841 9.3 23.9 44.4 120 15,689 7.8 18.2 33.0 121 16,362 19.1 29.9 45.3 122 13,813 6.2 15.4 28.3 123 32,769 50.8 72.5 100.0 124 15,657 11.3 21.7 36.4 125 32,606 21.3 43.0 73.6 126 20,695 36.6 50.3 69.7 127 16,020 7.0 17.6 32.7 128 18,891 8.6 21.2 38.9 129 19,063 0.0 12.7 30.6 130 28,151 33.3 52.0 78.5 131 22,937 23.1 38.3 59.8 132 0 0.0 0.0 0.0 133 0 0.0 0.0 0.0 134 31,137 52.4 73.1 100.0

C-2

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 135 20,468 20.2 33.8 53.1 136 16,222 0.0 10.8 26.0 137 0 0.0 0.0 0.0 138 13,547 10.7 19.7 32.4 139 24,359 18.8 35.0 57.9 140 32,830 34.1 55.9 86.7 141 17,179 0.0 11.4 27.5 142 15,943 5.3 15.9 30.9 143 16,364 17.2 28.1 43.4 144 20,698 17.7 31.5 50.9 145 16,416 30.0 40.9 56.3 146 19,996 28.2 41.5 60.3 147 14,933 9.5 19.4 33.5 148 14,829 0.0 9.9 23.8 149 15,009 7.2 17.1 31.2 150 13,984 10.3 19.5 32.7 151 0 0.0 0.0 0.0 152 19,653 5.2 18.3 36.7 153 16,226 6.9 17.7 32.9 154 15,785 8.6 19.1 33.9 155 17,877 15.2 27.1 43.9 156 24,664 19.9 36.3 59.5 157 17,705 9.7 21.5 38.1 158 14,548 14.2 23.8 37.5 159 23,728 32.6 48.4 70.6 160 15,699 0.0 10.4 25.2 161 17,086 15.4 26.8 42.8 162 17,342 4.8 16.3 32.6 163 15,963 20.7 31.3 46.3 164 23,426 33.3 48.9 70.9 165 22,116 8.2 22.9 43.6 166 23,773 26.7 42.5 64.8 167 21,176 5.8 19.9 39.7 168 15,626 5.9 16.2 30.9 169 23,155 17.6 32.9 54.7 170 14,347 0.0 9.5 23.0 171 18,425 11.7 23.9 41.2 172 16,879 11.3 22.6 38.4 173 16,944 9.3 20.6 36.5 174 17,613 9.7 21.4 37.9 175 22,296 0.0 14.8 35.7 176 21,879 22.3 36.8 57.4 177 13,844 7.0 16.2 29.2 178 16,735 5.3 16.4 32.1 179 15,191 11.9 21.9 36.2 180 19,133 22.9 35.6 53.6 181 16,523 11.4 22.3 37.9 182 18,991 14.3 26.9 44.7 183 16,203 4.5 15.3 30.5 184 15,546 5.7 16.1 30.7 185 19,375 13.7 26.5 44.7 186 17,987 7.3 19.3 36.2 187 18,998 5.4 18.0 35.8 188 22,090 0.0 14.7 35.4 189 13,914 6.5 15.7 28.8 190 19,751 12.9 26.1 44.6 191 18,952 13.6 26.2 44.0 192 16,145 10.3 21.0 36.2 193 18,770 5.4 17.9 35.5 194 15,561 7.6 17.9 32.5 195 13,168 3.4 12.1 24.5 196 14,080 7.4 16.8 30.0 197 17,205 6.1 17.5 33.7 198 21,286 4.9 19.1 39.1 199 14,279 3.6 13.1 26.5 200 15,201 12.7 22.8 37.1 201 10,625 0.0 7.1 17.0 202 13,243 10.2 19.0 31.4 203 12,742 8.0 16.5 28.4

C-3

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 204 18,425 15.0 27.2 44.5 205 13,962 6.0 15.3 28.4 206 14,459 5.6 15.2 28.7 207 0 0.0 0.0 0.0 208 23,066 30.0 45.3 67.0 209 20,485 17.0 30.6 49.8 210 17,944 16.5 28.4 45.3 211 14,388 2.5 12.1 25.6 212 18,484 25.0 37.3 54.7 213 19,183 19.1 31.8 49.8 214 16,438 0.0 10.9 26.4 215 13,465 7.8 16.7 29.4 216 17,466 5.1 16.7 33.1 217 19,435 15.5 28.4 46.7 218 24,022 30.6 46.5 69.1 219 17,658 0.0 11.7 28.3 220 22,239 11.9 26.6 47.5 221 18,636 12.1 24.5 42.0 222 21,143 11.3 25.3 45.2 223 19,036 39.8 52.4 70.3 224 22,306 9.9 24.7 45.7 225 21,504 15.2 29.5 49.7 226 16,082 1.9 12.6 27.7 227 15,771 7.6 18.1 32.9 228 15,572 4.8 15.2 29.8 229 15,899 5.4 16.0 30.9 230 14,109 5.9 15.3 28.6 231 15,027 6.0 16.0 30.1 232 17,350 1.6 13.1 29.4 233 16,113 4.2 14.9 30.0 234 21,588 24.8 39.2 59.4 235 13,516 0.0 9.0 21.7 236 19,306 12.5 25.4 43.5 237 20,786 16.0 29.8 49.3 238 19,643 12.8 25.9 44.3 239 15,416 4.0 14.3 28.7 240 16,518 0.0 11.0 26.5 241 14,984 2.4 12.3 26.4 242 18,757 9.8 22.3 39.9 243 14,571 0.0 9.7 23.4 244 20,403 4.2 17.8 37.0 245 17,128 18.9 30.3 46.4 246 14,609 0.0 9.7 23.4 247 27,018 27.2 45.2 70.5 248 19,650 23.1 36.1 54.6 249 9,167 0.0 6.1 14.7 250 18,777 10.2 22.7 40.3 251 12,758 11.3 19.8 31.8 252 14,044 6.6 15.9 29.1 253 14,098 3.9 13.3 26.5 254 66,088 69.5 100.0 100.0 255 15,808 9.0 19.5 34.3 256 16,727 4.5 15.6 31.4 257 12,851 2.5 11.0 23.1 258 15,947 13.9 24.5 39.4 259 19,684 13.8 26.8 45.3 260 16,187 2.3 13.0 28.2 261 21,355 21.6 35.8 55.8 262 15,073 1.4 11.4 25.6 263 16,000 2.8 13.4 28.4 264 15,982 7.5 18.2 33.2 265 15,557 2.0 12.3 26.9 266 10,062 5.1 11.8 21.2 267 15,144 9.5 19.5 33.8 268 20,501 6.8 20.4 39.7 269 19,132 19.5 32.2 50.2 270 17,148 12.0 23.4 39.5 271 11,403 4.6 12.2 22.9 272 10,617 1.5 8.6 18.5

C-4

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 273 11,199 4.5 11.9 22.4 274 10,682 4.4 11.5 21.5 275 10,770 11.1 18.2 28.3 276 16,687 9.7 20.8 36.5 277 14,334 11.4 20.9 34.3 278 22,327 18.3 33.1 54.1 279 15,144 14.5 24.6 38.8 280 13,260 12.4 21.2 33.7 281 8,146 6.1 11.5 19.2 282 16,642 25.4 36.4 52.1 283 14,311 4.3 13.8 27.3 284 17,099 11.7 23.0 39.1 285 23,344 22.0 37.6 59.5 286 12,410 6.3 14.5 26.2 287 14,542 9.3 18.9 32.6 288 8,486 8.6 14.2 22.2 289 14,621 5.6 15.3 29.0 290 14,423 2.8 12.4 25.9 291 14,896 12.7 22.6 36.6 292 15,254 1.3 11.4 25.8 293 13,922 1.2 10.4 23.5 294 16,192 5.8 16.5 31.7 295 16,908 14.9 26.1 42.0 296 18,387 7.0 19.3 36.5 297 17,447 16.2 27.8 44.2 298 15,531 7.4 17.7 32.3 299 14,623 8.9 18.7 32.4 300 15,664 6.5 16.9 31.7 301 14,964 7.5 17.4 31.5 302 14,182 6.5 16.0 29.3 303 23,450 18.9 34.5 56.5 304 19,905 12.3 25.5 44.2 305 17,430 6.2 17.8 34.1 306 16,151 18.9 29.7 44.8 307 12,942 6.0 14.6 26.8 308 21,772 14.0 28.5 48.9 309 19,312 5.7 18.5 36.7 310 14,939 0.0 9.9 23.9 311 19,722 21.7 34.9 53.4 312 23,857 14.3 30.1 52.5 313 17,600 0.0 11.7 28.2 314 17,084 3.0 14.3 30.4 315 15,051 15.7 25.7 39.8 316 22,615 0.0 15.0 36.3 317 15,618 7.0 17.4 32.0 318 0 0.0 0.0 0.0 319 0 0.0 0.0 0.0 320 0 0.0 0.0 0.0 321 0 0.0 0.0 0.0 322 0 0.0 0.0 0.0 323 0 0.0 0.0 0.0 324 12,763 1.1 9.6 21.5 325 15,537 5.6 15.9 30.5 326 13,633 11.7 20.7 33.5 327 11,348 4.5 12.1 22.7 328 13,271 16.1 24.9 37.4 329 11,816 5.5 13.3 24.4 330 12,175 5.6 13.7 25.1 331 16,233 4.6 15.4 30.6 332 15,583 9.4 19.8 34.4 333 18,263 10.6 22.7 39.9 334 16,717 6.5 17.6 33.3 335 16,940 12.1 23.3 39.2 336 16,050 19.6 30.2 45.3 337 15,524 13.6 23.9 38.5 338 15,211 7.7 17.9 32.1 339 15,221 6.7 16.8 31.1 340 19,004 15.9 28.6 46.4 341 15,091 7.5 17.6 31.7

C-5

Average Household Income Car Owning Household Rate (%) Zone in 2014 (PHP/month) 2014 Actual 2025 Model 2035 Model 342 14,607 19.8 29.5 43.2 343 12,648 12.1 20.5 32.4 344 17,266 8.3 19.8 36.0 345 15,010 14.3 24.2 38.3 346 17,386 7.7 19.2 35.6 347 21,380 12.0 26.2 46.3 348 27,675 26.1 44.5 70.4 349 17,671 11.0 22.7 39.3 350 15,028 12.4 22.4 36.5 351 16,185 9.6 20.4 35.6 352 15,615 16.1 26.5 41.1 353 11,990 13.4 21.3 32.6 354 13,553 0.0 9.0 21.7

C-6